Facilitating scalable 2-way mobile AV communications

ABSTRACT

A bandwidth management system for multiple-service mobile networks for use with a plurality of instances of mobile communications devices. A plurality of communications silo each provide at least one communications service using a mobile network wherein at least one communications service from at least one communications silo involving the transport of real-time two-way video. Call/session state information from the communications silos and packet-level network transport measurement information responsive to packet-level network transport processes in the mobile network are used by a control system to create control messages transmitted to the communications silos for controlling call/session admission application QoS parameters responsive to traffic and network operation.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application claims benefit of priority of U.S. Provisional PatentApplication Ser. No. 61/398,818 filed on Jun. 30, 2010, incorporatedherein by reference.

COPYRIGHT AND TRADEMARK NOTICES

A portion of the disclosure of this patent document may containmaterial, which is subject to copyright protection. Certain marksreferenced herein may be common law or registered trademarks of theapplicant, the assignee or third parties affiliated or unaffiliated withthe applicant or the assignee. Use of these marks is for providing anenabling disclosure by way of example and shall not be construed toexclusively limit the scope of the disclosed subject matter to materialassociated with such marks.

FIELD OF THE INVENTION

The invention pertains to mobile real-time 2-way audio-videocommunications and similar or related media (animations, visualizations,audio-video editors etc.) employing high performance communications formobile applications, and more specifically to technical approaches tonetwork technology and mobile devices for these so as to make associatedapplications and telecommunications services commercially viable morequickly than would otherwise occur via natural market and technologyevolution trends.

BACKGROUND OF THE INVENTION

The present invention is directed to mobile real-time 2-way audio-videocommunications and similar or related media (animations, visualizations,audio-video editors etc.) employing high performance communications formobile applications, and more specifically to technical approaches tonetwork technology and mobile devices for these so as to make associatedapplications and telecommunications services commercially viable morequickly than would otherwise occur via natural market and technologyevolution trends.

“Mobile Devices” and “Wireless Devices:” Terminology and Networking

In this discussion “mobile devices” are viewed as communications devicescomprising at least high radio frequency networking provided by cellularcommon-carrier providers, while “wireless devices” are devicescomprising at least high radio frequency networking provided by local“WiFi” networks. Examples of “mobile devices” include but are notlimited to smartphones, cellphones, Personal Digital Assistants (PDAs),tablet computers, and laptop computers

Some smartphones, cellphones, and other types of portable devices onlyoperate as mobile devices. Other types of portable devices only operateas wireless devices. Some smartphones, cellphone, and other types ofportable devices can operate in multiple modes: as mobile devices, aswireless devices, or in some implementations as both wireless devicessimultaneously.

Types of Mobile and Wireless Video Services

Video services provided by mobile and wireless devices currently includeat least some form of the following:

-   -   Broadcast video reception (mobile/wireless TV)    -   Streaming video reception from servers (Flash, YouTube, etc.)    -   Live streaming video reception    -   Live broadcast video transmission    -   Two-way video conversations

Other bandwidth intensive and processor intensive services supportableby mobile and wireless devices include at least:

-   -   Interactive animations (Google Earth & Street View)    -   High-speed file download    -   High-speed file upload

As mobile and wireless device technology improve, future bandwidthintensive and processor intensive capabilities supportable by mobile andwireless devices are likely to include at least:

-   -   Multi-point two-way video conferencing    -   Encrypted two-way video conferencing    -   High-speed file upload

FIG. 1 depicts the current evolution of video services on mobiledevices.

Bandwidth Management in Enterprise and Mobile Networks

In the enterprise, bandwidth limitations come and go over time, but atthis writing there is a current crisis and with new high-bandwidthapplications, and this crisis uis likely to persist for quite a while(and certainly reoccur again). A number of innovative yet pragmatic andpractical solutions to bandwidth management in enterprise in networksare taught in U.S. Pat. No. 7,738,492 and pending U.S. patentapplication Ser. Nos. 12/828,145 and 61/503,053.

Mobile networks will increasing need to support advanced applicationswith extensive bandwidth needs, creating a bandwidth need explosionagainst limited available spectrum. In mobile networks, typically thereis a permanent bandwidth limitation due to limited spectrum.Fine-grained reuse has been one solution, but not adequate in manysituations and has its own ultimate limitations despite introductions ofspatially-bounded bandwidth re-use strategies (micro-cells, pico-cells,femto-cells, etc.) causing acute impending needs for bandwidthmanagement.

Value of the Present Invention

The present invention first modifies and adapts the teachings of U.S.Pat. No. 7,738,492 and pending U.S. patent application Ser. Nos.12/828,145 and 61/503,053 for use providing bandwidth management toadvanced applications in mobile networks, and further buildssynergistically upon those foundations with new capabilities.

SUMMARY OF THE INVENTION

Features and advantages of the invention will be set forth in thedescription which follows, and in part will be apparent from thedescription, or may be learned by practice of the invention. Theobjectives and other advantages of the invention will be realized andattained by the structure particularly pointed out in the writtendescription and claims hereof as well as the appended drawings.

In an embodiment, the invention provides for adaptations of multiservicebandwidth management systems such as those taught in U.S. Pat. No.7,738,492 and pending U.S. patent application Ser. Nos. 12/828,145 and61/503,053 to be combined with congestion control methods and systemsdeveloped for wireless networks, as well as with other componenttechnologies, to synergistically create a practical, highly scalablemulti-service environments comprising video for mobile devices.

In an embodiment, the invention provides for adaptations of protocolgateways and transcoders to support aspects of highly scalablemulti-service environments comprising video for mobile devices.

In an embodiment, the invention provides for adaptations of videomultipoint bridges to support aspects of highly scalable multi-serviceenvironments comprising video for mobile devices.

In an embodiment, the invention provides for adaptations of real-timedata collaboration to support aspects of highly scalable multi-serviceenvironments comprising video for mobile devices.

In an embodiment, the invention provides for adaptations of real-timedata collaboration multipoint bridges to support aspects of highlyscalable multi-service environments comprising video for mobile devices.

In an embodiment, the invention provides for adaptations of one-wayvideo messaging (for example, video-mail) to support aspects of highlyscalable multi-service environments comprising video for mobile devices.

In an embodiment, the invention provides for bandwidth associatedmulti-service resource management systems such as those taught inpending U.S. patent application Ser. No. 12/828,145 to supportadditional aspects of highly scalable multi-service environmentscomprising video for mobile devices.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and advantages of the presentinvention will become more apparent upon consideration of the followingdescription of preferred embodiments, taken in conjunction with theaccompanying drawing figures, wherein:

FIG. 1 depicts the current evolution of video services on mobiledevices.

FIG. 2, adapted fromhttp://en.wikipedia.org/wiki/IP_Multimedia_Subsystem, depicts an examplerepresentation of an architectural overview of the 3GPP/TISPAN IPMultimedia Subsystem (IMS).

FIG. 3, adapted fromhttp://en.wikipedia.org/wiki/IP_Multimedia_Subsystem, depicts an examplerepresentation of Home Subscriber Server (HSS) within the 3GPP/TISPAN IPMultimedia Subsystem (IMS) architecture.

FIG. 4, adapted from http://en.wikipedia.org/wiki/UMTS, depicts anexample representation of the UMTS Network Architecture.

FIG. 5, adapted from http://en.wikipedia.org/wikWideo_share, depicts anexample representation of the IP Multimedia System (IMS) enabled “VideoShare” service for mobile networks.

FIG. 6 depicts adaptations and combinations of multiservice bandwidthmanagement technology, rate-adaptation congestion control methods, A/Vgateway technologies, and thin-client A/V technologies to createmultiservice mobile networks and devices supporting 2-way video.

FIG. 7 depicts the exemplary far more rapid evolution of AV mobileservices that include 2-way video, resulting in less waste, quickerrevenue streams, and avoidance of false starts.

FIG. 8 depicts an exemplary block diagram of an mobile networkingenvironment 100 including a representation of an exemplary mobilecommunication network 120 and a Communications Silos Environmentcomprising a plurality of communication silos 130 a-130 n, eachpertaining to a separate service-specific bandwidth reservation system.

FIG. 9 shows a “pie chart” representation depicting of how, at anyparticular moment in time, each of the bandwidth slices internallycomprises both used bandwidth and unused bandwidth.

FIG. 10 shows a macro-scale view showing all unused bandwidth beingaggregated contiguously.

FIG. 11 shows a “pie chart” view of how bandwidth allocation can beadjusted.

FIG. 12 depicts an exemplary high-level view of an exemplary UnifiedBandwidth Manager for controlling the maximum settings of each of thebandwidth reservation systems as provided for and as expanded by thepresent invention.

FIG. 13 a depicts a first level of abstraction of arrangements such asthat depicted in FIG. 12.

FIG. 13 b depicts a higher level of abstraction of arrangements such asthat depicted in FIG. 12 wherein the Unified Bandwidth Manager andCommunications Silo Environment are aggregated as a single controllingentity.

FIG. 14, FIG. 15, and FIG. 16 illustrate an exemplary regulation systemwithin the Unified Bandwidth Manager.

FIG. 17 illustrates a system including a Unified Bandwidth Manager, ashared resource and a plurality of framework controllers.

FIGS. 18 a-18 c depict the construction of a sequence of representations(“state-spaces”) of instantaneous service usage (or service demand) thatcan be used for resource allocation.

FIG. 19, adapted from [X1], illustrates examples of mixed bit-ratetraffic call or session capacity blocking behaviors and their generalstructure for non-extreme ranges of parameters to each service.

FIG. 20 a illustrates the arrangement of FIG. 18 b modified so as toinclude minimum bandwidth allocations to each service.

FIG. 20 b illustrates the arrangement of FIG. 18 c modified so as toinclude minimum bandwidth allocations.

FIG. 21 a shows how a single service inverse blocking algorithm can beused with the arrangement depicted in FIG. 20 a.

FIG. 21 b illustrates how a multiple service inverse blocking algorithmcan be used with the arrangement depicted in FIG. 20 b.

FIG. 22 and FIG. 23 depict exemplary ways the Unified Bandwidth Managercan internally calculate maximum call and session admission settings foreach of the bandwidth reservation systems.

FIG. 24 depicts an example implementation of a reservation system for amultiservice network wherein a “global” control system provides updatesto the each of the gateways as to the maximum number of calls/sessionseach service is to permit.

FIG. 25 depicts an example arrangement wherein information setting themaximum number of currently permitted calls/sessions for each serviceand the number of currently active calls/sessions can be exchanged amongcommunications silos through use of a shared database or shared files

FIG. 26 depicts an example arrangement wherein information setting themaximum number of currently permitted calls/sessions for each serviceand the number of currently active calls/sessions can be exchanged amongcommunications silos through direct peer-to-peer communications amongthe communications silos.

FIG. 27 depicts a representation generalizing various arrangements forrealizing adaptive reservation control environments.

FIG. 28 depicts an example of how such a “global” control system canmanipulate the maximum number of calls/sessions each service is topermit so as to create a reservation system.

FIG. 29 depicts example shaded sub-regions of reservation regions areunfair to the other service(s).

FIG. 30 depicts example alternative reservation boundary shapes.

FIG. 31 depicts an example arrangement wherein the basic sessionadmission closed-loop control system also variably controls call/sessionrate allocation made at the beginning of each new call/sessionallocation.

FIG. 32 depicts an example call/session admission closed-loop controlsystem.

FIG. 33 depicts an example of a multiple-layer control implementationwith no coordination between call/session admission control and QoScontrol.

FIG. 34 depicts an example of a multiple-layer control implementationwith coordination between call/session admission control and QoScontrol.

FIG. 35 depicts an example implementation of a SIP/H.323 protocolgateway as taught in pending U.S. patent application Ser. No. 12/572,226

FIG. 36 depicts an exemplary arrangement augmenting the exemplaryarrangement depicted in FIG. 13 b in an exemplary manner provided for bythe invention.

FIG. 37 depicts an example where an exemplary node within an exemplarymobile communications network comprises a router linking network dataflows inside the node with network data flows outside the node.

FIG. 38 shows exemplary state-space modifications and/or truncations ofthe product-form state-space and/or state-transitions.

DETAILED DESCRIPTION

In the following, numerous specific details are set forth to provide athorough description of various embodiments. Certain embodiments may bepracticed without these specific details or with some variations indetail. In some instances, certain features are described in less detailso as not to obscure other aspects. The level of detail associated witheach of the elements or features should not be construed to qualify thenovelty or importance of one feature over the others.

Further, in the following detailed description reference is made to theaccompanying drawing figures which form a part hereof, and which show byway of illustration specific embodiments of the invention. It is to beunderstood by those of ordinary skill in this technological field thatother embodiments may be utilized, and structural, electrical, as wellas procedural changes may be made without departing from the scope ofthe present invention.

1. Preliminaries

1.1 Current Evolution of Mobile and Wireless Video Services

Video services provided by mobile and wireless devices currently includeat least some form of the following:

-   -   Broadcast video reception (mobile/wireless TV)    -   Streaming video reception from servers (Flash, YouTube, etc.)    -   Live streaming video reception    -   Live broadcast video transmission    -   Two-way video conversations

Other bandwidth intensive and processor intensive services supportableby mobile and wireless devices include at least:

-   -   Interactive animations (Google Earth & Street View)    -   High-speed file download    -   High-speed file upload

As mobile and wireless device technology improve, future bandwidthintensive and processor intensive capabilities supportable by mobile andwireless devices are likely to include at least:

-   -   Multi-point two-way video conferencing    -   Encrypted two-way video conferencing    -   High-speed file upload

WiFi networks (used by wireless devices) currently provide far greaterbandwidth than cellular networks (used by mobile devices). Efforts areconstantly afoot to increase the bandwidth of both WiFi networks andcellular networks.

Current migrations plans span 3G, LTE, 4G, and into early proposals for5G.

FIG. 1 depicts the current evolution of video services on mobiledevices.

1.2 Network Environments in Supporting Video

FIG. 2, adapted fromhttp://en.wikipedia.org/wiki/IP_Multimedia_Subsystem, depicts an examplerepresentation of an architectural overview of the 3GPP/TISPAN IPMultimedia Subsystem (IMS).

FIG. 3, adapted fromhttp://en.wikipedia.org/wiki/IP_Multimedia_Subsystem, depicts an examplerepresentation of Home Subscriber Server (HSS) within the 3GPP/TISPAN IPMultimedia Subsystem (IMS) architecture.

FIG. 4, adapted from http://en.wikipedia.org/wiki/UMTS, depicts anexample representation of the UMTS Network Architecture.

FIG. 5, adapted from http://en.wikipedia.org/wiki/Video_share, depictsan example representation of the IP Multimedia System (IMS) enabled“Video Share” service for mobile networks.

1.3 Programming Environments in Supporting Video

It is noted that most application programming environments for thesetypes of devices are inefficient high-level programming languageimplementations in languages that do not directly run the processors inthe device. The rational here is that most applications are relativelylight-weight and by aligning the application development environmentwith widely familiar languages considerably lowers the barriers toapplications development are significantly reduced, effectively openingup 3^(rd)-party applications development to an extremely larger pool ofapplication designers (in contrast to providing an applicationsdevelopment environment based on the native assembly-level language ofthe embedded processor CPU, which would be the approach to maximize theefficiency of software execution). Examples of such applicationprogramming environments aligned with widely familiar languages include:

-   -   iPhone: ObjectiveC (within iOS/iPhone OS)    -   Blackberry: Java    -   Android: Java

An important exception to the preceding are application developmentenvironments for the Symbian operating system developed by a consortialed by Nokia. The Symbian operating system provides an adapted form ofC/C++ which importantly runs natively on the CPU(s) within smartphonesmanufactured by Nokia and Sony/Ericsson. Further, the NokiaSymbian-based smartphones provide the application programmer with directaccess to the media processors(s) within the handheld device. A coupleof other mentions are provide:

-   -   Web OS is a Linux-based mobile operating developed for use with        smartphones and tablet computers. It replaces Palm OS (also        called Garnet OS) which was a preceding Linux-based mobile        operating system originally directed to Personal Digital        Assistants (PDAs) manufactured by then developed by Palm, Inc.        (now Hewlett-Packard) and accordingly arranged to facilitate        touchscreen user interfaces.    -   Windows Phone 7 is a mobile operating system developed by        Microsoft, as successor to the earlier Windows Mobile platform        (although Windows Mobile applications are not supported on        Windows Phone 7). It provides a user interface, a specialized        typography-based design language (“Metro”), and integrates        operating system features with services and hardware control,        but has no multitasking capabilities.        1.4 Tradeoffs Among Network Bandwidth, Algorithms, Frame Rate,        Image Resolution, Processing Speed, and Power Consumption in        Supporting Video

Power consumption is a major issue in smartphones, cellphone, and othertypes of portable mobile and/or wireless handheld devices. The majorconsumers of energy are algorithmic processing and active visualdisplay. Real-time two-way audio-video communications require both.Reductions in media bandwidth diminishes the amount of data to process,but media compression/decompression is typically algorithmicallyintensive.

Video decompression is far simpler and less computationally intensivethan video compression. For this reason many contemporary smart-phonesand some higher-end cell-phones can support display of received video.Much of this is streaming video, such as YouTube views, “television”broadcast, and one-way video from video conferencing, typified by theoffering from Fring™. Because the computational load for videodecompression is relatively modest, video decompression applications canbe supported by the inefficient application programming languagesprovided for most mobile handheld devices.

Higher frame rates and higher resolutions increase the amount of networkbandwidth and processing power required (hence also increasing powerconsumption). Portable devices typically have small screens so the pixelcount (and thus image resolution) can be considerably less than that for2-way video on computers and in conference rooms.

1.5 Opportunities for Accelerated Deployment and Evolution of MobileVideo and Related Services

FIG. 1 depicts the current evolution of video services on mobiledevices.

FIG. 6 depicts adaptations and combinations of multiservice bandwidthmanagement technology, rate-adaptation congestion control methods andsystems A/V gateway technologies, and thin-client A/V technologies tocreate multiservice mobile networks and devices supporting 2-way video.

FIG. 7 depicts the exemplary far more rapid evolution of AV mobileservices that include 2-way video, resulting in less waste, quickerrevenue streams, and avoidance of false starts.

In an embodiment, the invention provides for adaptations of multiservicebandwidth management systems such as those taught in U.S. Pat. No.7,738,492 and pending U.S. application Ser. Nos. 12/828,145 and61/503,053 to be combined with congestion control methods and systemsdeveloped for wireless networks, as well as with other componenttechnologies, to synergistically create a practical, highly scalablemulti-service environment for mobile devices.

2. Bandwidth Management Control Systems Frameworks

It is noted that this section comprises material adapted from theteachings in U.S. Pat. No. 7,738,492 and pending provisional U.S. PatentApplication 61/503,053 but which have been modified for mobile servicesto form integrative and synergetic aspects and capabilities along withother parts of the invention

FIG. 8 depicts an exemplary block diagram of the mobile networkingenvironment 120 including a representation of an exemplary mobilecommunication network 100 and a Communications Silos Environment 130comprising a plurality of communication silos 130 a, 130 b, 130 c, . . ., 130N, each communication silo associated with and/or pertaining to atleast one separate service-specific bandwidth reservation system. Themobile networking environment 120 can also include one or more of VPNs,Intranets, the Internet, Extranets, etc.

In an embodiment provided for by the invention, each communication silois uniquely associated with and/or pertains to a separateservice-specific bandwidth reservation system. In another embodimentprovided for by the invention, at least one of the communication silosis associated with and/or pertains to more than one separateservice-specific bandwidth reservation system. In another embodimentprovided for by the invention, at least two of the communication silosare associated with and/or pertain to more the same service-specificbandwidth reservation system (for example, as can be advantageous inserver and/or network load balancing, security structuring, vendorenvironment segregation, product-vintage version segregation, etc.).

In contemporary product offerings and known proposed systems, each suchbandwidth reservation system carves out a dedicated portion of theoverall network bandwidth available in the mobile for exclusive use byone or more applications. That is, by definition adopted above, eachbandwidth reservation system is provided with a dedicated pool of mobilenetwork bandwidth for the exclusive use of a service associated withthat particular bandwidth reservation system. In applications wheresession admission control is used, rather than call admission, theinternal details and sharing effects can differ but for the sake ofillustration a session admission system can be viewed in this model as acommunications silo (such as 130 a, 130 b, 130 c, . . . , 130N.)comprising a bandwidth reservation system.

In practice, commercial bandwidth reservation system products and thereforeseen progeny are largely “black boxes” providing one or more ofvaried levels, types, and forms of controls, internal control systems,information, and internal dynamics. In particular, the internal controlsystems and internal dynamics will typically not be known.

The upper portion of FIG. 9 provides a “pie chart” 300 view representinghow mobile network bandwidth is carved up among some number of theseservices, the number here represented as the variable “N.” Each slice320 a, 320 b, 320 c, . . . , 320N of the pie 300 associated with theseservices (Service 1, Service 2, . . . Service N) represents a portion ofbandwidth reserved for the labeled service, i.e., reserved for theexclusive use of each associated bandwidth reservation system toallocate to calls or sessions. The remaining mobile network bandwidth310 remains available for general purpose use, outside the scope andreach of the communications silos 130 a, 130 b, 130 c, . . . , 130N andtheir associated services. As a result, its bandwidth is not used bythese N services.

The lower portion of FIG. 9 shows a “pie chart” view 300 of how, at anyparticular moment in time, each of the bandwidth slices 320 a, 320 b,320 c, . . . , 320N internally comprises both unused bandwidth 321 a,321 b, 321 c, . . . , 321N and used bandwidth 322 a, 322 b, 322 c, . . ., 322N. As any of this unused bandwidth 321 a, 321 b, 321 c, . . . ,321N is not made available for other services, it is effectively wasted.Should the demand for a particular service exceed the total amountcarved out for that service, any further requests for that service mustbe denied. This is the case even if there is unused bandwidth 321 a, 321b, 321 c, . . . , 321N in the isolated bandwidth pools of othercommunications silos 130 a, 130 b, 130 c, . . . , 130N.

FIG. 10 shows a macro-scale view 400 showing all unused bandwidth 321 a,321 b, 321 c, . . . , 321N on the left side as in FIG. 9 and on theright side reorganized so as to be contiguously aggregated. If there area large number of services, or inappropriate sizes in the carve-outs foreach service, there can be tremendous wastes of bandwidth. On the otherhand, if the carve-outs for each particular service are not largeenough, that service could suffer a high frequency of request rejectionsand denial of service. In fact, classic properties of blocking-policyresource allocation systems and methods confirm worse-case fears—withfixed bandwidth partitions and partitions of service requests, there isless efficiency and steep trade-offs between the amount of wastedbandwidth required to be kept in reserve versus the increases inblocking of service requests.

FIG. 11 depicts a recasting of the ‘fixed-boundary’ “pie chart” view 300of FIG. 9 as a variable boundary' “pie chart” view 500 wherein bandwidthallocation for each service can be dynamically adjusted as suggested bythe dashed arrowed lines 501-507. These dynamic adjustments can bedetermined or controlled by higher level policies, human operation,automatic hierarchical control systems, etc.

U.S. Pat. No. 7,738,492 teaches systems and methods for sucharrangements. More specifically, U.S. Pat. No. 7,738,492 teaches, amongother things, exemplary systems and methods for a Unified BandwidthManager for monitoring and for controlling the affairs of a plurality ofsuch bandwidth allocation communications silos. The control capabilitiestaught include:

-   -   human-operator control,    -   assistance to human-operator control, and    -   automatic control.        The above list and remarks are only exemplary and not to be        taken as limiting.

The Unified Bandwidth Manager, or “Meta-Gatekeeper,” taught U.S. Pat.No. 7,738,492 teaches a wide number of ways in which dynamicaladjustment of the size of individual bandwidth allocations, as suggestedby the dashed arrowed lines 501-507 in FIG. 11, can be made to each ofthe bandwidth reservation systems. In an embodiment provided for by theinvention, the Unified Bandwidth Manager provides a unified managementinfrastructure for all mobile network real-time communications (such asvideo conferencing).

In an embodiment provided for by the invention, the Unified BandwidthManager is capable of spanning many types of mobile communicationsservices.

FIG. 12 depicts an exemplary representation of exemplary embodiments ofthe Unified Bandwidth Manager as taught in U.S. Pat. No. 7,738,492 andas both provided for by the present invention and to be expanded by thepresent invention. More specifically, FIG. 12 depicts an exemplaryhigh-level view of an exemplary Unified Bandwidth Manager forcontrolling the maximum settings of each of the bandwidth reservationsystems as provided for and as expanded by the present invention. In thedepiction of FIG. 12, exemplary embodiments of the Unified BandwidthManager 110 interact with the plurality of bandwidth reservation systemsincluded in the plurality of communication silos 130 a, 130 b, 130 c, .. . , 130N. Exemplary embodiments of the Unified Bandwidth Manager 110can provide, for example, unified bandwidth management functions thatinclude call admission control functionality for all real-time trafficon mobile networking environment 120, which can include VPNs, Intranets,the Internet, Extranets, and so on. The real-time IP packet traffic caninclude VoIP, video conferencing, video streaming, e-mail, internet,internal applications, and so on. Exemplary embodiments of the UnifiedBandwidth Manager 110 can also interact with associated networkresources relating to other applications.

Exemplary embodiments of the Unified Bandwidth Manager 110 provide anintegration layer atop a plurality of real-time communicationstechnologies—more specifically atop a plurality of bandwidth reservationsystems. Depending upon implementation details and available informationflows, such an integration layer makes possible a number of functionsand features in the areas of administration, bandwidth management, andcost reductions.

Exemplary embodiments of the Unified Bandwidth Manager 110 interfacewith various outside gatekeeper, manager, and proxy server products andstandards. These include, but are not limited to, communications systemsbuilt on SIP, H.323 gatekeepers for voice and/or video, VoIP callmanagers, and Content Delivery Networks.

Exemplary embodiments of the Unified Bandwidth Manager 110 also providesa common network topology model and associated bandwidth pools, a singleinterface for administrators to describe their networks, a singleinterface for administrators to manage real-time communications, and asingle interface for deeply-embedded QoS infrastructure.

FIG. 13 a depicts a first level of abstraction of arrangements such asthat depicted in FIG. 12. At this level of abstraction, exemplaryinternal features, structures, etc. are suppressed. FIG. 13 b depicts ahigher level of abstraction of arrangements such as that depicted inFIG. 12 wherein the Unified Bandwidth Manager and Communications SiloEnvironment are aggregated as a single controlling entity 700.

FIG. 14 illustrates a regulation system 1250. Regulation system 1250 canbe used to represent selected aspects of commercial bandwidthreservation system products afore discussed. A controller 1200 takes acontrolling action 1201 on a phenomenon or resource 1202 (here relatingto call admissions, bandwidth usage, etc.) its current state is observedby an observation entity 1203 (usually called “observer” by thoseskilled in the art). The observer 1203 observes measures, monitors 1204the controlled phenomenon or resource 1202 by means or methodsappropriate and provides observation information 1205 to the controller1200 in a form the controller can use to control the phenomenon orresource 1202. The controller 1200 in this model is further providedwith desired goal information 1206. For example, a home heating systemtaken as such a system 1200 would have home air serving as phenomenon orresource 1202, a thermostat setting serving as desired goal information1206, a temperature sensor serving as observer 1203, the air temperatureserving as the measurement means 1204, an electrically-controlledheating unit serving as the controller 1200, and the signal from thetemperature sensor (observer 1203) to the heating unit (controller 1200)serving as observation information 1205. The controller 1200 interactionwith the phenomenon or resource 1202 has an inherent type of dynamics(in the home heating example, how long it takes the running heating unitto raise the temperature by 1 degree in a designated part of the home)and the resulting feedback loop 1201, 1204, 1205 with these controllerdynamics and observer 1203 characteristics produce a closed-loopbehavior (for example, a heating temperature undershoot or overshootthat causes discomfort in some part of the home separate from thetemperature sensor until the room temperature throughout the homestabilizes).

The controller 1200 is additionally provided with policy parameterinformation 1207 that can be used to control the behavior of the closedloop control system 1250. For the home heating example, the heating unitcan pulsate on or off with a varying duty cycle that can be adjusted forthe particulars of the home, or a hysteresis gap in the heater responsethan can be narrowed or widened according to the particulars of thehome. It is typically not feasible to provide a wide range of policies,so in practice there is a selection of policies or a collection ofpolicy variables that can be adjusted. In FIG. 14 these are thereforerepresented as “policy parameters” 1207.

FIG. 15 illustrates a regulation system 1350. FIG. 15 is similar to FIG.14 except that in FIG. 15, a second observer 1313 is also added forobserving, measuring, and/or monitoring 1314 the phenomenon or resource1302 and producing observation information 1315 directed to a goalcontroller 1316 that adjusts the desired goal 1306 in the systemdepicted in FIG. 14. In the home heating example, observer B 1313 cannote that the air is too cool for someone with an illness who is in thehouse, and adjust the temperature setting accordingly. For a givendesired goal setting, the inner feedback loop 1301, 1304, 1305 with thecontroller dynamics and observer characteristics produce a closed-loopbehavior like the framework system depicted in FIG. 14.

FIG. 16 illustrates a regulation system 1450. FIG. 16 is similar to FIG.15 except that in FIG. 16, a third observer 1313 is also added forobserving, measuring, and/or monitoring 1414 the phenomenon or resource1402 and producing observation information 1415 directed to a policycontroller 1416 that adjusts the policy 1407 in the systems depicted inFIG. 14 and FIG. 15. For example, in the home heating example, thecontroller 1400 can include adjustable parameters as to how long the fanruns after the heating element is turned off and a pause time before theheating element is turned on again. Observer C 1425 can monitor thetemperature in various parts of the home, and the policy controller canadjust these fan intervals and pause interval settings based on theinformation 1425 from Observer C 1423.

In reference to FIG. 16, in some embodiments, the goal observer 1413 andgoal controller 1416 functions are provided by a Unified BandwidthManager, such as Unified Bandwidth Manager 110, to a controller 1400. Insome embodiments, the policy observer 1423 and policy controller 1426functions are provided by a Unified Bandwidth Manager, such as UnifiedBandwidth Manager 110, to a controller 1400.

FIG. 17 illustrates a system 1500 including a Unified Bandwidth Manager1505, a shared resource 1502 and a plurality of framework controllers1510, 1520 and 1530. In some embodiments, the framework controllers1510, 1520 and 1530 are those as discussed above with reference to FIG.14. In some embodiments, each framework controller 1510, 1520 and 1530respectively controls an associated portion 1512, 1522, 1532 of commonshared resource 1502, such as mobile network bandwidth.

Needs for various types of services can vary, but typically eachbandwidth reservation system product at the very least would comprise atleast the controller 1510, 1520, 1530 and observer 1513, 1523, 1533entities and the desired goal settings 1516, 1526, 1536. Most wouldadditionally include at least some type of observer information path1515, 1526, 1536, and at least some would utilize the resulting feedbackloop. In this case, the desired goal settings 1516, 1526, and 1536correspond to the maximum allowed number of calls or sessions for theassociated service, as described earlier. Additionally, some productswould also provide for policy parameter settings 1517, 1527, 1537, and,in reference to FIG. 16, can even internal provide some type ofassociated policy-oriented observer 1423 and observation 1425 directedto a policy controller 1426 so as to provide a policy feedback loop.

In some embodiments, the Unified Bandwidth Manager 1505 provides atleast the policy observer and goal controller functions, such as policyobserver 1423 and goal controller 1416 functions of FIG. 16, to at leastthe plurality of the controllers 1510, 1520, 1530 depicted in FIG. 17.

In some embodiments, the Unified Bandwidth Manager 1505 provides atleast the policy observer 1423 and goal controller 1426 functionsdepicted in FIG. 16 to at least a plurality of controllers 1510, 1520,1530 depicted in FIG. 17. In some embodiments, the Unified BandwidthManager 1505 provides at least observers 1513, 1523, 1533 depicted inFIG. 17.

3. Controlling Call Admission, Session Admission, and Underlying SharedMobile Bandwidth

With these structural aspects of the hierarchical control systemestablished, attention is now directed to how call admission, sessionadmission, and underlying shared mobile bandwidth are controlled so asto realize the adjustable bandwidth allocations described earlier inconjunction with FIG. 11. FIGS. 18 a-18 c depict the construction of asequence of geometric mathematical representations (“state-spaces”) ofinstantaneous service usage (or service demand) that can be used forstochastic blocking-oriented performance prediction and other types ofshared-constraint resource allocation computations. FIG. 18 a depicts acase where there is only a single service, FIG. 18 b depicts a case withtwo services, and FIG. 18 c depicts a case with three services.

FIG. 18 a depicts a case with only a single service “Service 1.” Forexample, Service 1 can be a VoIP service operated under the control ofan associate bandwidth reservation system. In FIG. 18 a, the amount ofbandwidth carved out for Service 1 determines the maximum number ofService 1 VoIP calls that can be allowed. This sets a maximum permittedextreme 1612 on a single axis or scale 1611 associated with Service 1.At any moment in time, the number of active calls (or in another type ofdesign, demand for calls) lies at a point 1613 on this axis or scale1611 in the interval between the zero value 1600 and the maximumpermitted extreme 1612. The amount of unused bandwidth carved out onlyfor Service 1 and not available to other bandwidth reservation systemscomprised by other communications silos is the interval 1614 bounded bythe number of active calls 1613 and the maximum permitted extreme 1612.

FIG. 18 b expands the single service case of FIG. 18 a into anarrangement accommodating two services, Service 1 and Service 2. Here,two scales or axes are used, one axis 1611 for Service 1 and anotherorthogonal axis 1621 for Service 2. At any moment in time, the number ofactive calls for Service 1 lies at a point 1613 on this axis or scale1611 in the interval between the zero value 1600 and the maximumpermitted extreme 1612. Similarly, at any moment in time, the number ofactive calls for Service 2 lies at a point 1623 on this axis or scale1621 in the interval between the zero value 1600 and the maximumpermitted extreme 1622. Here, by virtue of control by the UnifiedBandwidth Manager, such as Unified Bandwidth Manager 110, unusedbandwidth is pooled into a common group 1625 for potential reallocation.Because the total bandwidth used in this two service system must be thesum of the bandwidth used by Service 1 and bandwidth used by Service 2,the boundary for the permissible combinations is a line segment withnegative slope 1620 connecting the external values 1612, 1622 forService 1 and Service 2.

FIG. 18 c expands the single service case of FIG. 18 a and the dualservice case of FIG. 18 b into an arrangement that accommodates threeservices, Service 1, Service 2, and Service 3. Here, three scales oraxes are used, one axis 1611 for Service 1, another orthogonal axis 1621for Service 2, and a third orthogonal axis 1631 for Service 3. At anymoment in time, the number of active calls for Service 1 lies at a point1613 on this axis or scale 1611 in the interval between the zero value1600 and the maximum permitted extreme 1612. Similarly, at any moment intime, the number of active calls for Service 2 lies at a point 1623 onthis axis or scale 1621 in the interval between the zero value 1600 andthe maximum permitted extreme 1622. Similarly, at any moment in time,the number of active calls for Service 3 lies at a point 1633 on thisaxis or scale 1631 in the interval between the zero value 1600 and themaximum permitted extreme 1632. Again, by virtue of control by theUnified Bandwidth Manager, such as Unified Bandwidth Manager 110,bandwidth not used by Service 1, Service 2 and Service 3 can be pooledinto a common group 1635 for potential reallocation. Because the totalbandwidth used in this two service system must be the sum of thebandwidth used by Service 1, the bandwidth used by Service 2, and thebandwidth used by Service 3, the boundary for the permissiblecombinations is a triangular plane section with negative slope 1630connecting the external values 1612, 1622, 1632 for Service 1, Service 2and Service 3.

This procedure depicted in FIGS. 216 a-216 c can be extended to includemore services with associated bandwidth reservation system so as toproduce state spaces with higher dimensions. The limiting point 1612 inFIG. 18 a, limiting line segment 1622 in FIG. 18 b, and limiting planesection 1632 of FIG. 18 c generalize to a hyperplane of dimension oneless than the number of services in a state space whose number ofdimensions equal the number of services. The respect line segment, area,and volume of FIGS. 216 a-216 c bounded by the axes, the zero point1600, and the limiting point/line/plane are respectively one, two, andthree dimensional simplexes. All possible permissible combinations ofallocations across the services lie within or on the borders of thesesimplexes. For N services, then, all permissible allocation combinationswithin the control of the combination of the Unified Bandwidth Manager,such as Unified Bandwidth Manager 110, with the N instances of bandwidthreservation system products controlled by the Unified Bandwidth Manager,such as Unified Bandwidth Manager 110, lie within such an N-dimensionalsimplex. It is important property that the points within such a simplexof any dimension can readily be sequenced by nesting of counting loops(such as a “DO-loop”) as is well known to those familiar computerprogramming. For example, for an N-dimensional simplex, N separatenested “DO-loops” can be used with interdependent iterating countinglimits.

In the case of calls and sessions such as the Unified Bandwidth Manager,such as Unified Bandwidth Manager 110, and controlled bandwidthreservation system products would expect to manage, it is empiricallycommon that, at least piece-wise in time throughout the business day,call and session requests arrive independently of one another. Thisgives rise to fairly accurate modeling of the time behavior of incomingrequests for calls and sessions, within at least piece-wise segments ofthe business day, by a stochastic process known as the Poisson process.Similar independence structures can be used to model the duration oftime the call or session; these lead to an exponential probabilitydistribution for the call or session duration. Together these create awell-vetted process for modeling blocking and resource allocations. Ascall arrival rates vary during a business day (for example busy hour,lunch hour, special events), a single parameter in the Poisson rate canbe adjusted and the model will still largely apply.

Note this mathematical structure fits the call and session requestprocess quite well, but does not apply to the time process for theunderlying generation of individual packets. The number of active callsand sessions will modulate the rates of underlying packet generation,and thus directly correspond to a time-average of packet loading.However, in general the statistics of individual packet generation ratesis quite different from a Poisson arrival/exponential duration model. Insome embodiments the Unified Bandwidth Manager, such as UnifiedBandwidth Manager 110, can model the time process of individual packetgeneration.

For calculating what level of blocking probability that call and sessionrequests would be expected to experience for a single serviceexclusively drawing from shared resource (i.e., the case of FIG. 18 a),well-know formulas and functions such as those attributed to and knownas Erlang and Engset are used. It turns out that these formulas can bequite forgiving of the duration time probability distribution.Importantly, well-known algorithms are available for numericallycalculating these Erlang and Engset blocking formulas.

For calculating what amount of resource available in the shared resourcepool drawn upon by call or session requests of a single service so as toguarantee a maximum level of blocking, the Erlang and Engset blockingformulas can be inverted. Such inversion can be accomplished by puttingan algorithm for the Erlang and Engset blocking formulas within aconditional counting loop, but other more sophisticated algorithms arewidely known and can be readily applied by one skilled in the art oftelephone traffic engineering. The inverted Erlang and Engset blockingformulas will be used in some embodiments of the control system, butthey advantageously can be first extended to handle multiple services,particularly where the average bandwidth of each service is appreciablydifferent. This is commonly the case; a (one-way) streaming audiosession can use 16 kB to 32 kB per second, a (two-way) VoIP call can usetwice this range, and a (two-way) point-to-point video session can use200 kBps to 800 kBps.

If the empirically well-fitting Poisson arrival and exponential durationapproximate statistics are in fact utilized for more of theirmathematical power, they can be leveraged to address this problem. ThePoisson arrival/exponential duration statistics impose a time-reversalsymmetry, mathematically giving rise to an adjoint-like structure to thetransition probabilities between states. Theorems of Kelly and othersshow that a brute force transition probability lattice can beconstructed, only the points within the simplex need be kept, and thetotal sum of probabilities of each surviving state transitions can beused to renormalize the individual state transition probabilities.Further, this holds if the simplex is tilted in various ways. Thesimplex limit points at the axes can be scaled according to relativelyhow many service instances are permitted for the associated servicemultiplied by the relative amount of underlying resource one instance ofthat service uses. Thus, to handle multiple services with differingbandwidth requirements, call/session request arrival rates, andcall/session durations, quite simple algorithms, very similar to thoseto numerically compute single service Erlang and Engset blockingformulas, can be used. Further, the average call/session arrival ratemultiplied by the average call duration provides a well-known quantitycalled the traffic intensity, and this traffic intensity quantity is allthat is needed from traffic observations for blocking calculations.

These properties will leverage further to address fairness amongallocations within the collection of services. First, some examples areprovided for applying the above to a two-service system.

One of the results of sharing bandwidth between services with differingbandwidth requirements is that services requiring higher bandwidth percall or session will experience a higher blocking probability thanservices requiring lower bandwidth per call or session. This can beappreciated using the last example: two higher resource sessions require16 units of resource. If there are more than 4 lower resource sessionsactive, less than 16 units of resource would be available. The moregeneral phenomenon is suggested by FIG. 19. FIG. 19, adapted from [X1]and created by Lyndon Ong based on the formulas of [X2], illustratesexamples of cases where freely sharing bandwidth between services withdiffering bandwidth requirements results in the services requiringhigher bandwidth per call or session will experience a higher blockingprobability than services requiring lower bandwidth per call or session.Details here also depend on relative service request arrival rates foreach type of service, and although there are notable curve variations aswell as pathologies and exceptions, FIG. 19 illustrates examples ofmixed bit-rate blocking behaviors and their general structure fornon-extreme ranges of parameters. Families of blocking probabilitycurves are shown for the “higher-resource service” 1810 and“lower-resource service” 1820. For each family of curves, the blockingprobability 1801 decreases 1811, 1812 with increasing numbers of totalshared resource, as is almost always the case in shared resourceenvironments. However, the two families of curves 1810, 1820 spread withincreasing divergence as the ratio 1802 of resource required increases,showing an increasingly unfair advantage for the “lower-resourceservice.”

One way to make allocations and denials fairer, and in general have morepredictable operation, is to impose minimum bandwidth allocations, suchas, limit the number of resources that can be monopolized by any oneservice in the bandwidth sharing. This can be done by hacking awayregions of the simplex of permitted shared bandwidth states.

FIG. 20 a shows truncation of the simplex of FIG. 18 b that can be usedto guarantee minimum bandwidth allocations for each service and thusreinstate fairness in a mixed bandwidth system that would otherwiseexhibit the dynamics illustrated in FIG. 19. The constraint boundary forthe full sharing in FIG. 18 b has been replaced with a minimum bandwidthallocation boundary 1924, 1924 a, 1924 b truncating the states permittedby the original end-regions 1925 a, 1925 b associated with the ‘open’policy with the minimum bandwidth allocation boundaries 1924 a, 1924 bcorresponding to reservation levels 1921, 1922. These truncating minimumbandwidth allocation levels are dictated by the minimum bandwidthallocation constraints 2Y<Ymax (for Y boundary 1925 a at intercept 1921)and 8X<Xmax (for X boundary 1925 b at intercept 1922).

These reservation constraints can be calculated from algebraic equationsresulting from various fairness policies. This results in anon-triangular region of permissible states 1952. The reservationconstraints depicted in the two-service case of FIG. 18 c are relativelyminor; more severe reservation effects are electively demonstrated inFIG. 20 b. In particular, FIG. 20 b shows the effect of reservationscutting off large portions of the surface of the geometric simplex ofFIG. 18 c, resulting in truncation planes 1944 a, 1944 b, 1944 c withintercepts 1941, 1942 and 1943. In this example, the reservations are sosignificant that only a small portion 1944 of the original open surface1934 of the geometric simplex depicted in FIG. 20 b remains. (In thelimit, stringent reservations effectively eliminate resource sharing,transforming the region of permissible states into a cube whose outwardvertex shares only one point with the original open surface 1934 of thesimplex.)

To summarize, sharing services across multiple services with differingbandwidth, arrival rates, and duration statistics can readily beaccounted for in the Kaufmann or related model by straightforwardshifting of simplex vertices and renormalization of the remainingrelative state transition probabilities. Fairness can be provided for bytruncating the simplex in the manner described in FIGS. 20 a-20 b. Asdescribed earlier, these blocking probability algorithms can beinverted, at least through embedding the within blocking probabilityalgorithms conditional counting loops. In an embodiment the resultinginverted formula algorithms can be used to calculate the bandwidthneeded to ensure the blocking probabilities required for each servicegiven the observed call or session arrival rates for each service. In anembodiment, the Kaufmann or related model can be used for “scratchpad”calculations for an algorithm or interactive user interface operated byan administrator to explore “what if” cases of various candidateadmission policy situations.

With this foundation, the power of the geometric state space and simplexmanipulation representation of bandwidth sharing and reservations comesdirectly into play. Shifting or truncating the simplexes is equivalentto simple manipulation of the limits of “DO-loops”. The mathematicsinherent in the model formulas handles everything else within arenormalization factor. The renormalization factor is directly computedby sequencing the “DO-loops” so as to sum every state transitionprobability among neighboring states within the simplex. These systemsand methods to be incorporated in embodiments of the Unified BandwidthManager, such as Unified Bandwidth Manager 110.

The Unified Bandwidth Manager 110, can use these types of invertedblocking probability algorithms in various ways to automaticallyreadjust the bandwidth carved out for each of the bandwidth reservationsystems as a function of the traffic pattern observations. The simplersingle-service Erlang and Engset inverted blocking probabilityalgorithms can be used to estimate the bandwidth carve-out needed for aspecified call or session request refusal rate (i.e. blockingprobability) and traffic intensity.

FIG. 21 a shows how single service inverse blocking algorithm associatedwith FIG. 20 a can be used to emulate the real-world service experienceprovided by each individual bandwidth reservation system. FIG. 21 aillustrates a flow chart for using this type of algorithm 2040 in thisway. With an instance of the arrangement of FIG. 21 a for each service,the Unified Bandwidth Manager, such as Unified Bandwidth Manager 110,can predict the amount of bandwidth 2050 each bandwidth reservationsystem in each of the plurality of communication silos will require tobe carved out given currently observed (or forward predicted) trafficintensity 2020 associated with that communication silo service for aspecified level of blocking performance 2010.

FIG. 21 b illustrates now a multiple service inverse blocking algorithmassociated with FIG. 20 b can be used to emulate the real-world serviceexperience provided by a bandwidth reservation system.

FIG. 21 b shows an extension of the arrangement of FIG. 21 a utilizingan algorithmic inversion 2090 of the Kelley/Kauffman multiple serviceblocking calculations described earlier. For each service, currentlyobserved (or forward predicted) traffic intensity 2021-2029 andspecified level of blocking performance 2011-2019 are specified. Themultiple service algorithmic inversion 2090 provides the amount ofbandwidth 2051-2059 each bandwidth reservation system in each of theexemplary plurality of communication silos will require to be carvedout. Additionally the multiple service algorithmic inversion 2090provides the ability to guarantee minimum bandwidth allocations2031-2039 to ensure fairness should that feature be useful to theUnified Bandwidth Manager feature set. Through mathematical manipulationthese fairness settings can also be used in other contexts, includingthe maximum call bounds associated with each bandwidth reservationsystem.

The Unified Bandwidth Manager 110 can use these in various ways tointernally calculate maximum bandwidth settings for each of thebandwidth reservation systems. One embodiment is depicted in FIG. 22.FIG. 22 depicts an exemplary embodiment of ways the Unified BandwidthManager 110 can internally calculate maximum call and session admissionsettings for each of the bandwidth reservation systems. Here, anallocation module 2160 can obtain information 2184 from trafficobservations, information 2184 from an aggregate bandwidth allocationusage model 2180, and external administration information 2184. Trialhigh-level allocation decisions are directed to a parameter generationmodule 2170 that provides parameters suitable to send to the bandwidthreservation systems. These control parameter settings are instead sentto single service models 2141-2149 of the bandwidth reservation systems.These are as described in conjunction with FIG. 21 a, and produce theresulting bandwidth requirement loads they need to guarantee theirassociated performance levels. These resulting bandwidth requirementloads are combined, potentially with other model outputs andconsiderations, in the aggregate bandwidth allocation usage model 2180.

In some embodiments, the allocation module 2160 can interact with themultiple service model 2190 so as to include broader inter-serviceinteraction effects and fairness-oriented considerations in theallocation decisions made by the allocation model 2160.

FIG. 23 depicts an embodiment of ways for the Unified Bandwidth Managerto internally calculate maximum bandwidth settings for each of thebandwidth reservation systems. FIG. 23 depicts a variation of thearrangement of FIG. 22 wherein behavioral models 2241, 2242 and 2249have been enhanced with additional service-specific attributes and whichpass additional service-specific considerations 2286 to the allocationdecision module 2292.

In some embodiments, allocation decision module 2292 is similar toallocation module 2160, except it additionally includes any of thefollowing additional components and methods: empirical predictors fortraffic variations (trend based, time-of-day based, event based, etc.),empirical behavior models for unknown dynamics of a bandwidthreservation system product, topological considerations regardingspecific communication Links and Site networks, failure handling,recovery, and post-failure allocation, topological call-based routing,and merger of like communications silos and associated traffic that aresegregated into separate administrative domains.

In some embodiments, the Unified Bandwidth Manager 110 can include oneor more of traffic predictors and empirical behavior models for unknowndynamics of bandwidth reservation system products. Empirical predictorsfor traffic variations (trend based, time-of-day based, event based,etc.) are known in the art. These can comprise formal system estimationand/or time-series models. In some embodiments, the Unified BandwidthManager 110 can include various forms of these. Empirical behaviormodels for unknown internal dynamics of a dynamical system are known inthe art. These can be applied to estimating the unknown internaldynamics of a bandwidth reservation system product. In some embodiments,the Unified Bandwidth Manager, such as Unified Bandwidth Manager 110,includes various forms of these.

At the level of simply granting or denying a new incoming call/sessionrequest, there are at least two approaches that can be employed:

-   -   Approaches wherein the admission control system is not involved        with or responsive to packet level processes (considered in this        section), and    -   Approaches wherein the admission control system is involved with        and/or responsive to packet level processes (considered Section        6).

Because the underlying media is packet-oriented, admission controlsystems that are not involved with or responsive to packet levelprocesses treat each call/session a particular service type as if itoccupies or consumes some sort of bandwidth footprint, (i.e. an“effective bandwidth” value, “average bandwidth” value, “peak bandwidth”value, etc.), that is an abstract block of bandwidth for eachcall/session of a particular service type. This is as was discussed inthe opening portions of this document, but is brought forward as areminder here.

3.1 Example Architectures for Implementing Adaptive Admission ControlReservations

As just described in the previous section, a control system providedwith at least call/session state information can be used to implement afixed or adaptive reservation system across multiple services on acommon network by manipulating the settings for the maximum number ofsimultaneously active calls/sessions for each participating gatekeeper,applications, or other aspects within each individual communicationsservice silo. The control and measured information flows of such asystem can be implemented, for example, as depicted in FIG. 24.Alternatively, the reservation system can be implemented without acentralized controller through use of a shared database or shared files(as suggested by FIG. 25), direct peer-to-peer communications among thecommunications silos (as suggested by FIG. 26), as well as otherpossible approaches.

For arrangements such as depicted in FIG. 24, there are at least twoapproaches for incorporating adaptive control given that a controlsystem is already in place. In one approach, the fixed reservationcontrol system is replaced by an adaptive reservation control system, ormodified so as to provide adaptive reservation control capabilities.

In a second approach to incorporating adaptive control into arrangementssuch as that depicted in FIG. 24, the fixed reservation control systemin FIG. 24 is arranged to be in turn controlled by an additional controlsystem that can modulate the fixed reservation settings. Inputs to theadditional control system are not shown in but can include one or moreof:

-   -   the same information provided to the global controller,    -   subsets of the information provided to the global controller,    -   additional information provided by the communications silos    -   additional information obtained by additional estimators and/or        network monitor measurements of traffic on the network.

For arrangements such as depicted in FIG. 25, an external adaptivereservation control system can communicate with the shared database orshared files. Inputs to the additional control system are not shown inbut can include one or more of:

-   -   additional information provided by the communications silos    -   additional information obtained by additional estimators and/or        network monitor measurements of traffic on the network.

For arrangements such as depicted in FIG. 26, an external adaptivereservation control system can communicate with each of thecommunications silos. Inputs to the additional control system are notshown in but can include one or more of:

-   -   additional information provided by the communications silos    -   additional information obtained by additional estimators and/or        network monitor measurements of traffic on the network.

FIG. 27 shows a representation generalizing each of the examplesdescribed in conjunction above (as well as others), as suggested by the2-service examples depicted in FIG. 28 the settings for each servicesilo's maximum number of simultaneously active calls/sessions can bewidely adjusted so as to ride the full-sharing boundary. If this is doneonly to specific limiting values, reservation systems with allowed statespaces can be implemented. If these limiting values are fixed (forexample, by a communications service administrator or networkadministrator, the result behaves a fixed reservation system, If insteadthese limiting values are allowed to vary under feedback control, theresult is an adaptive reservation system,

3.2 Control as a Function of Active Call/Session State

As a first example implementation of adaptive reservation control, thereservation boundaries can be changed as a function of the state. Therational for this is worthy of a brief philosophical aside:

-   -   The whole purpose of reservations is to guarantee a minimum        amount of bandwidth for a particular service when one or more        other services would otherwise consume all available shared        bandwidth;    -   However, if at least one service is experiencing high traffic        demands while one or more other services hardly have any usage,        then the result is unfair to the heavily loaded service(s), and        further is wasteful as the reserved bandwidth goes unused;    -   If the reservations are large, or there are many services with        reservations, then the waste and unfairness can become        extensive.        A moment's reflection on the above points yields at some point        that reservation arrangements provide some of what is desired        for a service but in fact too much protection for that service        in that some portions of the reservations are excessive. As a        start to this, consideration of the example presented in FIG. 29        shows that at least most of the shaded sub-regions of the        reservation regions are unfair to the other service(s). Thus the        problem with fixed reservations is that the reservation region        has the wrong-shaped boundary. Further review of desired policy        can produce more desirable boundary shapes for the reservations        region. For example, in FIG. 30 the reservation boundary        associated with Service 1 is sloped at a different angle than        the corresponding reservation boundary of FIG. 29, and the        reservation boundary associated with Service 1 comprises at        least one breakpoint. In general forms of this arrangement as        provided for by the invention, state information can be used to        control the maximum number of calls/sessions so as control the        shapes of the reservation boundaries in arbitrary ways.        Typically, however, it is advantageous to have whatever the        resulting shape of the entire bold curve be convex (for as shown        in [X2] non-convex shapes can give rise to unrealistic and/or        undesired outcomes).

In another example implementation, conditional tests are performed onthe values of current-state input, the outcome of the conditional testscausing the generation of a control message to change the maximum numberof calls/sessions for at least one service.

3.3 Quantizing and Hysteresis

With quick reference to FIG. 14C, it can be seen that the angular-slopedportions of the bold curves in FIG. 29 and FIG. 30 require an ongoingflux (and typically a high number) of communications messages from thecontroller to the individual communications silos as the state changesfrom one state value to another. Also, importantly, it can be seen thatthe arrangement of FIG. 30 requires a higher number of communicationsmessages from the controller to the individual communications silos thanthe arrangement of FIG. 29—this is because the reservation regions ofFIG. 29 will not require further communications messages from thecontroller until the state leaves these regions). One signature of thelatter circumstance is that a reservation boundary is parallel to acoordinate axes.

Thus, the number of messages can be reduced if the various slopesdepicted in the arrangements of FIG. 29 and FIG. 30 and theirhigher-dimensional generalizations are quantized into staircases (fortwo services) or more generally (for three or more services) quantizedinto convex hulls with surfaces parallel to planes defined by pairs ofcoordinate axes. The greater the level of this form of quantization, theless message flux required from the controller to the individualcommunications silos so as to adjust the maximum number ofcalls/sessions for each service as suggested in FIG. 24. In order toreduce the message flux from the controller to the individualcommunications silos, the quantization process is implemented in thecontroller.

Another way to reduce the message flux is to employ hysteresis in theadjustment of the maximum number of calls/sessions for each service. Inone example implementation, the hysteresis process introducesdirectional memory into the adjustment process of the maximum number ofcalls/sessions for each service. In order to reduce the message fluxfrom the controller to the individual communications silos, thehysteresis process is implemented in the controller. Yet otherarrangements are possible, anticipated, and accordingly provided for bythe invention.

3.4 Controller Dynamics Considerations

In the situations described thus far, the call/session request dynamicscan cause the state to vary widely, so much so that only use of currentstate (i.e., the current number of active calls/sessions at a giveninstant) may result in both erratic behavior and a high flux of controlmessages. One approach to improve these shortcomings would be to includethe rate-of-change of the state (i.e., the rate-of-change of the numberof active calls/sessions at a given instant) as an input to the adaptivereservation controller. This allows, for example, the observance of highrates-of-change in the state (current number of active calls/sessions ata given instant) to cause anticipatory adjustments in relevantreservation settings.

In an example implementation, the rate-of-change measurement can beimplemented as a simple difference between a previous state value andthe current state value. In another example implementation, therate-of-change measurement can be implemented as a more sophisticatednumerical difference operator approximating a time-derivative (forexample, multi-point stencil, difference quadrature, etc.).

In contrast to rate-of-change “time-derivative” controller input whichproduces anticipatory behavior, “time-integral” input can be used toproduce lagging conservative influences in the response. More generally,a weighted combination of current-state input, rate-of-change“time-derivative” input, and “time-integral” input can be used toproduce a response with more desirable dynamics. In the case of a linearcontroller, such an arrangement would correspond to a“Proportional/Integral/Derivative” or PID controller. The inventionprovides for use of linear PID controllers but also provides for the useof nonlinear PID controllers as advantageous in various applications.For example:

-   -   In an example implementation, a linear PID controller        (comprising separate weighting coefficients for current-state        input, rate-of-change “time-derivative” input, and        “time-integral” input) is arranged so that the weighting        coefficients are adjusted as function of state (for example,        with different anticipatory versus conservative lagging        behaviors when the state is nearer resource limit and        reservation boundaries than when the state is farther from these        resource limit and reservation boundaries;    -   In another example implementation, conditional tests are        performed on the values of current-state input and one or more        of rate-of-change “time-derivative” input and “time-integral”        input, the outcome of the conditional tests causing the        generation of a control message to change the maximum number of        calls/sessions for at least one service.

Many other dynamic control arrangements are possible and are providedfor by the invention. For example, the controller can comprise one ormore of:

-   -   A linear predictor;    -   A nonlinear predictor;    -   A traditional Kalman (Gaussian) filter;    -   A modified Kalman filter (for example, non-Gaussian)    -   A time-driven ramp generator;    -   A periodic or dithering function;    -   A quantization process;    -   A hysteresis process.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.        3.5 Stochastic Model Considerations

In another approach, the adaptive reservations controller can includeaspects structured around a model of the stochastic dynamics and/orstatistics of the call/session arrival and departure processes. Thesecan facilitate the advantage or need for providing the adaptivereservations controller with other types of input information. Forexample:

-   -   In one example implementation an adaptive reservations        controller can comprise aspects specifically designed around        mathematical expressions derived from models employing Markovian        dynamics. In such an arrangement, it can be advantageous to        provide the adaptive reservations controller with real-time        estimates of arrival rates and holding times.    -   As another example, an implementation an adaptive reservations        controller can comprise aspects based on Bayesian decision        theory. In such an arrangement, it can be advantageous to        provide the adaptive reservations controller with real-time        estimates of various probability distributions with respect to a        set of observations.    -   As yet another example, an implementation an adaptive        reservations controller can comprise aspects based on time        series data. In such an arrangement, it can be advantageous to        provide the adaptive reservations controller with real-time        estimates of various time series quantities with respect to a        set of observations.    -   As still another example, an implementation an adaptive        reservations controller can comprise aspects based on other        types of models, for example UPC parameters. In such an        arrangement, it can be advantageous to provide the adaptive        reservations controller with real-time tabulations of various        UPC parameter values and demographics with respect to the        currently active calls/sessions.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.        4. Adapting Wireless Rate-Adaptation Congestion Control Methods        and Systems to Mobile Networks

In an embodiment, the invention provides for adaptations of thin-clientAV methods and systems to support aspects of highly scalablemulti-service environments comprising video for mobile devices.

Attention is again directed to FIG. 6 depicts in part adaptations andcombinations of multiservice bandwidth management technology, A/Vgateway technologies, and rate-adaptation congestion control methods andsystems developed for wireless networks to create multiservice mobilenetworks and devices supporting 2-way video. Shown here is how thebandwidth management system controls the rate adaption parameters of oneor more rate-adaptation systems.

The arrangement can be further extended to control the bit-rateallocation for new calls/sessions (allocated at their admission), thusaffecting the bandwidth footprint of that particular session/call. Forexample, as traffic levels increase, new session/call requests areallocated less bandwidth.

FIG. 31 depicts an example adaptation of the arrangement of FIG. 32wherein the basic session admission closed-loop control system alsovariably controls call/session rate allocation made at the beginning ofeach new call/session allocation. An adaptive reservation controllercould be designed, as advantageous, to take various policy actions inresponse to current traffic, traffic measurements, call/sessionparameter demographics, traffic trends, etc.

As with adaptive call/session allocation reservation control, thecontrol of control the bit-rate allocation for new calls/sessions(allocated at their admission) could also be made to respond to networkpacket statistics. This approach is considered in Section 6.

4.1 Example Rate Allocation Control Actions and Policies

Some example actions and policies pertaining to actions for the controlof bit-rate allocations made at each new call/session acceptance caninclude the following (as well as mixtures, variations, and featurecombinations of these and others):

-   -   Admitting all new calls/session at higher bit rates when the        network is lightly loaded with active calls/sessions and        admitting all new calls/session at lower bit rates when the        network is more heavily loaded with active calls/sessions.    -   Admitting all new calls/session at higher bit rates when the        network is lightly loaded with active calls/sessions and        admitting some new calls/session at lower bit rates when the        network is more heavily loaded with active calls/sessions.    -   In cases where only some new calls/session are admitted at lower        bit rates, the selection could be made according to:        -   i. round-robin w/ fixed duty cycle        -   ii. round-robin w/ variable duty cycle    -   Admitting all new calls/sessions of certain types at higher bit        rates when the network is lightly loaded with active        calls/sessions and admitting all new calls/session of these        certain types or classes at lower bit rates when the network is        very heavily loaded with active calls/sessions (while admitting        all new calls/sessions of other at higher bit rates when the        network is lightly loaded with active calls/sessions and        admitting some new calls/session at lower bit rates when the        network is only somewhat heavily loaded with active        calls/sessions)

As with the aforedescribed call/session adaptive (admission)reservations controllers, rate allocation control actions can includesimilar types of features, attributes and behaviors as described below.

4.2 Control as a Function of Active Call/Session State

As a first example implementation of call/session rate allocationcontrol, the allocated rate can be changed as a function of the state.For example, conditional tests are performed on the values ofcurrent-state input, the outcome of the conditional tests causing thegeneration of a control message to change the bit rate allocated to newcalls/sessions for at least one service until the next update.

4.3 Quantizing and Hysteresis

The number of rate allocation control messages can be reduced if theallowed bit rates are quantized in some way, for example from a list ofstandardized values, a list of conveniently spaced values, or accordingto a mathematical quantization function. The greater the level of thisform of quantization, the less message flux required from the controllerto the individual communications silos. In order to reduce the messageflux from the controller to the individual communications silos, thequantization process is implemented in the controller. Another way toreduce the rate allocation control message flux is to employ hysteresisin the adjustment of the rate allocation for new calls/sessions for eachaffected service. In one example implementation, the hysteresis processintroduces directional memory into the rate allocation adjustmentprocess. In order to reduce the message flux from the controller to theindividual communications silos, the hysteresis process is implementedin the controller. Yet other arrangements are possible, anticipated, andaccordingly provided for by the invention.

4.4 Controller Dynamics Considerations

In the situations described thus far, the call/session request dynamicscan cause the state to vary widely, so much so that only use of currentstate (i.e., the current number of active calls/sessions at a giveninstant) may result in both erratic behavior and a high flux of controlmessages. One approach to improve these shortcomings would be to includethe rate-of-change of the state (i.e., the rate-of-change of the numberof active calls/sessions at a given instant) as an input to the adaptivereservation controller. This allows, for example, the observance of highrates-of-change in the state (current number of active calls/sessions ata given instant) to cause anticipatory adjustments in relevant rateallocation settings.

In an example implementation, the rate-of-change measurement can beimplemented as a simple difference between a previous state value andthe current state value. In another example implementation, therate-of-change measurement can be implemented as a more sophisticatednumerical difference operator approximating a time-derivative (forexample, multi-point stencil, difference quadrature, etc.).

In contrast to rate-of-change “time-derivative” controller input whichproduces anticipatory behavior, “time-integral” input can be used toproduce lagging conservative influences in the response. More generally,a weighted combination of current-state input, rate-of-change“time-derivative” input, and “time-integral” input can be used toproduce a response with more desirable dynamics. In the case of a linearcontroller, such an arrangement would correspond to a“Proportional/Integral/Derivative” or PID controller. The inventionprovides for use of linear PID controllers but also provides for the useof nonlinear PID controllers as advantageous in various applications.For example:

-   -   In an example implementation, a linear PID controller        (comprising separate weighting coefficients for current-state        input, rate-of-change “time-derivative” input, and        “time-integral” input) is arranged so that the weighting        coefficients are adjusted as function of state (for example,        with different anticipatory versus conservative lagging        behaviors when the state is nearer resource limit and        reservation boundaries than when the state is farther from        resource limit and reservation boundaries;    -   In another example implementation, conditional tests are        performed on the values of current-state input and one or more        of rate-of-change “time-derivative” input and        “time-integral”input, the outcome of the conditional tests        causing the generation of a control message to adjust bit rate        allocations.

Many other dynamic control arrangements are possible and are providedfor by the invention. For example, the controller can comprise one ormore of:

-   -   A linear predictor;    -   A nonlinear predictor;    -   A traditional Kalman (Gaussian) filter;    -   A modified Kalman filter (for example, non-Gaussian)    -   A time-driven ramp generator;    -   A periodic or dithering function;    -   A quantization process;    -   A hysteresis process.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.        4.5 Stochastic Model Considerations

In another approach, rate allocation control can include aspectsstructured around a model of the stochastic dynamics and/or statisticsof the call/session arrival and departure processes. These canfacilitate the advantage or need for providing the adaptive reservationscontroller with other types of input information. For example:

-   -   In one example implementation, rate allocation control can        comprise aspects specifically designed around mathematical        expressions derived from models employing Markovian dynamics. In        such an arrangement, it can be advantageous to provide the        adaptive reservations controller with real-time estimates of        arrival rates and holding times.    -   As another example, an implementation of rate allocation control        can comprise aspects based on Bayesian decision theory. In such        an arrangement, it can be advantageous to provide the rate        allocation control function with real-time estimates of various        probability distributions with respect to a set of observations.    -   As yet another example, an implementation of rate allocation        control can comprise aspects based on time series data. In such        an arrangement, it can be advantageous to provide the rate        allocation control function with real-time estimates of various        time series quantities with respect to a set of observations.    -   As still another example, an implementation of rate allocation        control can comprise aspects based on other types of models, for        example UPC parameters. In such an arrangement, it can be        advantageous to provide the rate allocation control function        with real-time tabulations of various UPC parameter values and        demographics with respect to the currently active        calls/sessions.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.

A number of rate adaption approaches can be employed by the invention,for example [Z1],[Z2],[Z3],[Z4].

5. Bandwidth Management at the Packet-Process (QoS) Level

It is noted that this section comprises material adapted from theteachings in pending provisional U.S. Patent Application 61/503,053 butwhich have been modified for mobile services to form integrative andsynergetic aspects and capabilities along with other parts of theinvention. Additional teachings applicable to the present invention arealso to be found in pending provisional U.S. Patent Application61/503,053.

Despite the immense gap between envisioned and available QoScapabilities, the extremely wide range of possible QoS capabilities, andthe possible extensive reach of QoS infrastructure (potentially threadedthrough applications, endpoint devices, operating systems, servers,network switches, routers, firewalls, and WANs), it is nonethelesspossible to incorporate QoS generically into a broader bandwidthmanagement control system as will be seen.

Just as the session/call admission and rate adaptation parameters can begoverned by closed-loop feedback control environment so as to increasenetwork performance towards the extreme limit possible by the policy towhich the control system is optimized, a similar closed-loop feedbackcontrol environment can be applied to QoS parameters.

As described below, the present invention provides for combiningclosed-loop feedback control of session/call admission and rateadaptation parameters with closed-loop feedback control of QoSparameters. The combinations can be made in various ways, for examplevia a multiple-layer control implementation with no coordination betweencall/session admission control and QoS control (for example, asrepresented in FIG. 33), as addressed in this section. Alternatively amultiple-layer control implementation with coordination betweencall/session admission control and QoS control (for example, asrepresented in FIG. 34) can be used, as addressed in Section 6.

An immense amount of analytical, standards, and technology developmentwork has been undertaken to explore the possibilities and capabilitiesof QoS for ATM and IP networks. On the technology development side, someQoS features are implemented to varying degrees in network products(such as IP switches) from major network equipment manufacturers. On thestandards side, earlier QoS standards material developed for ATM isbeing repurposed for IP networks. Some aspects, such as some IPCparameters, suffer from definitions and concepts that presentimplementation difficulties in practical product offerings. On theanalytical side, vast amounts of mathematical modeling, innovation,performance prediction, optimization, approximation, definitional,metric, simulation, and other work has been performed. This work wasinitially directed towards ATM and later repurposed, adapted, andcontinued for IP networks and more recently wireless and mobilenetworks. The creative solutions and mathematical prowess of theseresults are in many aspects truly astonishing and worthy of greatpraise. However, without any criticism or mount of prejudice, it hasturned precious few of these results lend themselves to direct use incurrent network technology. Many of the wide range of analytical resultshave nonetheless made important contributions to the conceptual base,behavioral understanding, definitional rigor, intuition, and designprinciples. With full respect to all the far reaching work performed byall camps, one reference providing practical QoS implementationapproaches in terms of contemporary product technology is the book byMiguel Barreiros and Peter Lundqvist entitled QOS-Enabled Networks:Tools and Foundations published 2010 by John Wiley & Sons, Ltd. [X4].

In practical QoS systems deployed in products from major networkequipment manufacturers typically [X5, X6, X7] perform functions suchas:

-   -   Identification of individual traffic flows/classes/groups;    -   Classification/reclassification these, for example:        -   using DiffSery Code Point (DSCP) field in IP packets;        -   using 802.1p Class of Service (CoS) field in Ethernet            packets;        -   source/destination IP or MAC address;        -   Layer 4 Transmission Control Protocol (TCP) ports;        -   User Datagram Protocol (UDP) ports;    -   Policing incoming packets;    -   Marking of incoming packets;    -   Traffic Shaping;    -   Rate Shaping;    -   Assigned to an appropriate outgoing switch queue;    -   Perform of scheduling input queue-servicing, for example:        -   Weighted Round Robin (WRR) scheduling;        -   Strict priority scheduling;    -   Dynamic creation of new classes of service;    -   Rate adaptation (in wireless 802.11 networking).

However, these provisions provided in contemporary networking productsare typically performed responsive to associated configuration QoSparameter settings made (and on rare occasion adjusted) by networkadministrators and are not varied over time by a control systemresponsive to network traffic conditions. In contrast, the presentinvention provides for such QoS parameter settings to be varied overtime by a control system responsive to network traffic conditions.Further, the actions taken by the afore-listed provisions provided incontemporary networking technology are (with the exception of rateadaptation) typically performed strictly within network-internal packettransport systems such as switches and routers. In contrast, the presentinvention provides for other QoS-related actions to be taken byapplications in some instances where advantageous,

A QoS parameter whose control has been studied and which at leastconceptually involves QoS-related actions taken by applications to bevaried over time responsive to network traffic conditions is rateadaptation as used in wireless 802.11 networks (wherein the bit rate ofan active call/session is changed from the bit-rate value initiallyallocated to a new bit-rate value). The invention provides for includingthe variation of bit rate at an application by a control system whereinthe variation is responsive to network traffic conditions. The inventionfurther provides for a control system that combines real-time control ofrate adaptation at applications together with real-time control ofpacket transport QoS parameters. In various situations it can beadvantageous to control these together, selectively or in combinationvarying one or both of these over time responsive to network trafficconditions.

Yet further, the present invention provides for QoS-related actionstaken by applications to be varied over time by a control systemresponsive to network traffic conditions. Aside from rate adaptation,this is not a direction taken by either the QoS community norapplications developers. However, such an approach could be useful insome situations, for example in real-time video encoding. In somecircumstances it could be advantageous to only adjust QoS-relatedactions taken by applications and this is anticipated and provided forby the invention. In most circumstances, however, it would be more beadvantageous for a common control system to vary both QoS parameters atapplications and packet transport QoS parameters at network elements,varying these over time responsive to network traffic conditions.

5.1 Example QoS Control Actions and Policies

Some example actions and policies pertaining to actions for the controlof QoS parameters can include the following (as well as mixtures,variations, and feature combinations of these and others):

-   -   Adjusting packet transport QoS parameters for calls/sessions        operating at higher bit rates.    -   Adjusting packet transport QoS parameters for all calls/sessions        of a particular service, class, or type.    -   Adjusting packet transport QoS parameters for only most recent        calls/sessions of a particular service, class, or type when the        network becomes loaded with active calls/sessions.    -   Admitting all new calls/session at higher bit rates when the        network is lightly loaded with active calls/sessions and        admitting some new calls/session at lower bit rates when the        network is more heavily loaded with active calls/sessions.    -   In cases where only some packet flows and/or applications are to        have QoS parameters adjusted, the selection could be made        according to:        -   i. round-robin w/ fixed duty cycle        -   ii. round-robin w/ variable duty cycle            5.2 Control as a Function of Active Call/Session State

As a first example implementation of QoS parameter control (at networkelements and/or at applications), QoS parameters can be changed as afunction of the state. For example, conditional tests are performed onthe values of current-state input, the outcome of the conditional testscausing the generation of a control message to change a QoS parameteruntil the next update.

5.3 Quantizing and Hysteresis

The number of QoS control messages can be reduced if the allowed bitrates are quantized in some way, for example from a list of standardizedvalues, a list of conveniently spaced values, or according to amathematical quantization function. The greater the level of this formof quantization, the less message flux required from the controller tothe individual communications silos. In order to reduce the message fluxfrom the controller to the individual communications silos, thequantization process is implemented in the controller. Another way toreduce QoS control message flux is to employ hysteresis in theadjustment of the rate allocation for new calls/sessions for eachaffected service. In one example implementation, the hysteresis processintroduces directional memory into the rate allocation adjustmentprocess. In order to reduce the message flux from the controller to theindividual communications silos, the hysteresis process is implementedin the controller. Yet other arrangements are possible, anticipated, andaccordingly provided for by the invention.

5.4 Controller Dynamics Considerations

In the situations described thus far, the call/session request dynamicscan cause the state to vary widely, so much so that only use of currentstate (i.e., the current number of active calls/sessions at a giveninstant) may result in both erratic behavior and a high flux of controlmessages. One approach to improve these shortcomings would be to includethe rate-of-change of the state (i.e., the rate-of-change of the numberof active calls/sessions at a given instant) as an input to the adaptivereservation controller. This allows, for example, the observance of highrates-of-change in the state (current number of active calls/sessions ata given instant) to cause anticipatory adjustments in relevant QoSparameters.

In an example implementation, the rate-of-change measurement can beimplemented as a simple difference between a previous state value andthe current state value. In another example implementation, therate-of-change measurement can be implemented as a more sophisticatednumerical difference operator approximating a time-derivative (forexample, multi-point stencil, difference quadrature, etc.).

In contrast to rate-of-change “time-derivative” controller input whichproduces anticipatory behavior, “time-integral” input can be used toproduce lagging conservative influences in the response. More generally,a weighted combination of current-state input, rate-of-change“time-derivative” input, and “time-integral” input can be used toproduce a response with more desirable dynamics. In the case of a linearcontroller, such an arrangement would correspond to a“Proportional/Integral/Derivative” or PID controller. The inventionprovides for use of linear PID controllers but also provides for the useof nonlinear PID controllers as advantageous in various applications.For example:

-   -   In an example implementation, a linear PID controller        (comprising separate weighting coefficients for current-state        input, rate-of-change “time-derivative” input, and        “time-integral” input) is arranged so that the weighting        coefficients are adjusted as function of state (for example,        with different anticipatory versus conservative lagging        behaviors when the state is nearer resource limit and        reservation boundaries than when the state is farther from        resource limit and reservation boundaries;    -   In another example implementation, conditional tests are        performed on the values of current-state input and one or more        of rate-of-change “time-derivative” input and “time-integral”        input, the outcome of the conditional tests causing the        generation of a control message to adjust bit rate allocations.

Many other dynamic control arrangements are possible and are providedfor by the invention. For example, the controller can comprise one ormore of:

-   -   A linear predictor;    -   A nonlinear predictor;    -   A traditional Kalman (Gaussian) filter;    -   A modified Kalman filter (for example, non-Gaussian)    -   A time-driven ramp generator;    -   A periodic or dithering function;    -   A quantization process;    -   A hysteresis process.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.        5.5 Stochastic Model Considerations

In another approach, QoS parameter control (at network elements and/orat applications) can include aspects structured around a model of thestochastic dynamics and/or statistics of the call/session arrival anddeparture processes. These can facilitate the advantage or need forproviding the adaptive reservations controller with other types of inputinformation. For example:

-   -   In one example implementation, rate allocation control can        comprise aspects specifically designed around mathematical        expressions derived from models employing Markovian dynamics. In        such an arrangement, it can be advantageous to provide a        controller of QoS parameter control (at network elements and/or        at applications) with real-time estimates of arrival rates and        holding times.    -   As another example, an implementation of rate allocation control        can comprise aspects based on Bayesian decision theory. In such        an arrangement, it can be advantageous to provide the QoS        control function with real-time estimates of various probability        distributions with respect to a set of observations.    -   As yet another example, an implementation of rate allocation        control can comprise aspects based on time series data. In such        an arrangement, it can be advantageous to provide the QoS        control function with real-time estimates of various time series        quantities with respect to a set of observations.    -   As still another example, an implementation of QoS parameter        control (at network elements and/or at applications) can        comprise aspects based on other types of models, for example UPC        parameters. In such an arrangement, it can be advantageous to        provide the QoS control function with real-time tabulations of        various UPC parameter values and demographics with respect to        the currently active calls/sessions.

Yet other arrangements are possible, anticipated, and accordinglyprovided for by the invention.

6. Joint Bandwidth Management Control Spanning Both the Call/SessionAllocation Level and Packet-Process (QoS) Level

It is noted that this section comprises material adapted from theteachings in pending provisional U.S. Patent Application 61/503,053 butwhich have been modified for mobile services to form integrative andsynergetic aspects and capabilities along with other parts of theinvention. Additional teachings applicable to the present invention arealso to be found in pending provisional U.S. Patent Application61/503,053.

As mentioned before, the invention provides closed-loop feedback controlof session/call admission parameters and packet-level process, forexample by closed-loop feedback control of QoS parameters. In Section 7,closed-loop feedback control of session/call admission parameters isdone in parallel and independently from the closed-loop feedback controlof QoS parameters. The closed-loop feedback control of session/calladmission parameters acts on a slower time-scale than the closed-loopfeedback control of QoS parameters. Each of the two control systems canbe separately optimized without coordination between them. Such anarrangement was depicted earlier as the example provided in FIG. 33.

In this section, the closed-loop feedback control of session/calladmission parameters is done together with the closed-loop feedbackcontrol of network QoS parameters. Such a control system acts on twotime-scales in a manner that permits a coordinated optimization of bothcourse and fine structure of bandwidth allocation and utilization. Suchan arrangement was depicted earlier as the example provided in FIG. 34.

Some examples of joint multiple-time-scale call/session and packet (QoS)closed-loop control include:

-   -   Control of rate adaptation (bit-rate of active calls/sessions        after their admission, thus changing the bandwidth footprint of        that particular active session/call) as a function of the number        and type of active calls/sessions. For example, as traffic        levels increase, various active sessions/calls are allocated        less bandwidth.    -   Combined closed-loop feedback control of session/call admission,        rate adaptation parameters, and network element QoS parameters.

Yet other arrangements are possible, anticipated, and accordinglyprovided for by the invention.

In principle, a number of methods can be used to construct a controlsystem operating at two such differing time scales. These include butare not restricted to:

-   -   Abstracting the faster (packet) dynamics into statistical        moments (averages, variances, etc.), extremal values, etc. to        create control signals for slower (call/session) dynamics    -   Abstracting the faster (packet) dynamics into extremal values to        create control signals for slower (call/session) dynamics    -   Abstracting the slower (call/session) dynamics to piecewise        constant controls to the faster (packet) dynamics    -   Use of rare events models    -   Use of singular perturbation techniques    -   Combinations of these among themselves and or with yet other        techniques.

Yet other arrangements are possible, anticipated, and accordinglyprovided for by the invention.

6.1 Example Control Actions and Policies

Some example actions and policies pertaining to actions for the controlof QoS parameters can include the following (as well as mixtures,variations, and feature combinations of these and others):

-   -   Adjusting packet transport QoS parameters for calls/sessions        operating at higher bit rates.    -   Adjusting packet transport QoS parameters for all calls/sessions        of a particular service, class, or type.    -   Adjusting packet transport QoS parameters for only most recent        calls/sessions of a particular service, class, or type when the        network becomes loaded with active calls/sessions.    -   Admitting all new calls/session at higher bit rates when the        network is lightly loaded with active calls/sessions and        admitting some new calls/session at lower bit rates when the        network is more heavily loaded with active calls/sessions.    -   In cases where only some packet flows and/or applications are to        have QoS parameters adjusted, the selection could be made        according to:        -   i. round-robin w/ fixed duty cycle        -   ii. round-robin w/ variable duty cycle            6.2 Control as a Function of Active Call/Session State

As a first example implementation of QoS parameter control (at networkelements and/or at applications), QoS parameters can be changed as afunction of the state. For example, conditional tests are performed onthe values of current-state input, the outcome of the conditional testscausing the generation of a control message to change a QoS parameteruntil the next update.

6.3 Quantizing and Hysteresis

The number of QoS control messages can be reduced if the allowed bitrates are quantized in some way, for example from a list of standardizedvalues, a list of conveniently spaced values, or according to amathematical quantization function. The greater the level of this formof quantization, the less message flux required from the controller tothe individual communications silos. In order to reduce the message fluxfrom the controller to the individual communications silos, thequantization process is implemented in the controller. Another way toreduce QoS control message flux is to employ hysteresis in theadjustment of the rate allocation for new calls/sessions for eachaffected service. In one example implementation, the hysteresis processintroduces directional memory into the rate allocation adjustmentprocess. In order to reduce the message flux from the controller to theindividual communications silos, the hysteresis process is implementedin the controller. Yet other arrangements are possible, anticipated, andaccordingly provided for by the invention.

6.4 Controller Dynamics Considerations

In the situations described thus far, the call/session request dynamicscan cause the state to vary widely, so much so that only use of currentstate (i.e., the current number of active calls/sessions at a giveninstant) may result in both erratic behavior and a high flux of controlmessages. One approach to improve these shortcomings would be to includethe rate-of-change of the state (i.e., the rate-of-change of the numberof active calls/sessions at a given instant) as an input to the adaptivereservation controller. This allows, for example, the observance of highrates-of-change in the state (current number of active calls/sessions ata given instant) to cause anticipatory adjustments in relevant QoSparameters.

In an example implementation, the rate-of-change measurement can beimplemented as a simple difference between a previous state value andthe current state value.

In another example implementation, the rate-of-change measurement can beimplemented as a more sophisticated numerical difference operatorapproximating a time-derivative (for example, multi-point stencil,difference quadrature, etc.).

In contrast to rate-of-change “time-derivative” controller input whichproduces anticipatory behavior, “time-integral” input can be used toproduce lagging conservative influences in the response. More generally,a weighted combination of current-state input, rate-of-change“time-derivative” input, and “time-integral” input can be used toproduce a response with more desirable dynamics. In the case of a linearcontroller, such an arrangement would correspond to a“Proportional/Integral/Derivative” or PID controller. The inventionprovides for use of linear PID controllers but also provides for the useof nonlinear PID controllers as advantageous in various applications.For example:

-   -   In an example implementation, a linear PID controller        (comprising separate weighting coefficients for current-state        input, rate-of-change “time-derivative” input, and        “time-integral” input) is arranged so that the weighting        coefficients are adjusted as function of state (for example,        with different anticipatory versus conservative lagging        behaviors when the state is nearer resource limit and        reservation boundaries than when the state is farther from        resource limit and reservation boundaries;    -   In another example implementation, conditional tests are        performed on the values of current-state input and one or more        of rate-of-change “time-derivative” input and “time-integral”        input, the outcome of the conditional tests causing the        generation of a control message to adjust bit rate allocations.

Many other dynamic control arrangements are possible and are providedfor by the invention. For example, the controller can comprise one ormore of:

-   -   A linear predictor;    -   A nonlinear predictor;    -   A traditional Kalman (Gaussian) filter;    -   A modified Kalman filter (for example, non-Gaussian)    -   A time-driven ramp generator;    -   A periodic or dithering function;    -   A quantization process;    -   A hysteresis process.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.        6.5 Stochastic Model Considerations

In another approach, QoS parameter control (at network elements and/orat applications) can include aspects structured around a model of thestochastic dynamics and/or statistics of the call/session arrival anddeparture processes. These can facilitate the advantage or need forproviding the adaptive reservations controller with other types of inputinformation. For example:

-   -   In one example implementation, rate allocation control can        comprise aspects specifically designed around mathematical        expressions derived from models employing Markovian dynamics. In        such an arrangement, it can be advantageous to provide a        controller of QoS parameter control (at network elements and/or        at applications) with real-time estimates of arrival rates and        holding times.    -   As another example, an implementation of rate allocation control        can comprise aspects based on Bayesian decision theory. In such        an arrangement, it can be advantageous to provide the QoS        control function with real-time estimates of various probability        distributions with respect to a set of observations.    -   As yet another example, an implementation of rate allocation        control can comprise aspects based on time series data. In such        an arrangement, it can be advantageous to provide the QoS        control function with real-time estimates of various time series        quantities with respect to a set of observations.    -   As still another example, an implementation of QoS parameter        control (at network elements and/or at applications) can        comprise aspects based on other types of models, for example UPC        parameters. In such an arrangement, it can be advantageous to        provide the QoS control function with real-time tabulations of        various UPC parameter values and demographics with respect to        the currently active calls/sessions.        Yet other arrangements are possible, anticipated, and        accordingly provided for by the invention.        7. Including Resources Other than Bandwidth in Bandwidth        Management in Call/Session Admissions

The following provides material adapted from the teachings in pendingU.S. patent application Ser. No. 12/828,145 which are modified formobile services to form integrative and synergetic aspects andcapabilities along with other parts of the invention.

In addition to network bandwidth allocations, many contemporarynetwork-based computer and communications services, applications, andcapabilities also involve the associated allocation of various types ofcommunications processing resources such as (but not limited to):

-   -   Protocol translating gateways (for example H.323/SIP gateways        such as those taught in pending U.S. patent application Ser. No.        12/572,226),    -   Signal transcoder Banks (for example H.263/Flash,        H.263/Quicktime, etc.),    -   Network firewalls,    -   Conference bridges (a.k.a. “MCUs”),    -   Media stream encryption engines.        as well as other types of server-based assets such as those        residing on (but not limited to):    -   Video storage servers    -   Media processing servers    -   Interactive map and GIS servers    -   Network-hosted application servers.

Using the simplified abstracted representation of FIG. 13 b as the pointof departure, the present invention is directed to expanding at leasttwo capabilities of the control environment provided by the exemplaryUnified Bandwidth Manager features and embodiments taught in pendingU.S. patent application Ser. No. 12/572,226, namely:

-   -   assistance to human-operator control, and    -   automatic control.

Within these the present invention provides for the inclusion ofassociated “network communications processing” resources such as (butnot limited to):

-   -   Protocol translating gateways (for example H.323/SIP gateways        such as those taught in pending U.S. patent application Ser. No.        12/572,226 and depicted in FIG. 35),    -   Signal transcoder banks (for example H.263/Flash,        H.263/Quicktime, etc.),    -   Network firewalls,    -   Conference bridges (a.k.a. “MCUs”),    -   Media stream encryption engines.

Additionally, the systems and methods can be extended to other types ofserver-based assets such as those residing on (but not limited to):

-   -   Video storage servers    -   Media processing servers    -   Interactive map and GIS servers    -   Network-hosted application servers.

Again, each of the lists and associate remarks provided above are merelyexemplary and are not to be taken as limiting.

In an embodiment, the invention provides for bandwidth associatedmulti-service resource management systems such as those taught inpending U.S. patent application Ser. No. 12/828,145 to support aspectsof highly scalable multi-service environments comprising video formobile devices.

FIG. 36 depicts an exemplary arrangement augmenting the exemplaryarrangement depicted in FIG. 13 b in an exemplary manner provided for bythe invention. In this exemplary arrangement, servers or otherconfigurations provide for instances of:

-   -   Protocol translating gateways sessions    -   Signal transcoder sessions    -   Network firewall traversal sessions    -   Conference bridges (a.k.a. “MCUs”) sessions.

The depicted collection of gateways, banks, firewalls, etc. is merelyexemplary—any of the above can be omitted or replaced with other typesof network communications processing resources and/or server-basedassets, for example (but not limited to):

-   -   Media stream encryption sessions    -   Video storage server sessions    -   Media processing server sessions    -   Interactive map server sessions    -   GIS server sessions    -   Network-hosted application server sessions.        Additionally, the depicted collection need not have pluralities        of gateways, banks, firewalls, etc., but can have one instance,        that instance capable of providing a plurality of sessions. A        contemporary network-based computer and communications service,        application, or capability can request or require bandwidth        allocations and additionally at least one associated allocation        of a communications processing resource such as those listed        above. The invention provides for at least some of these        allocations to be directly or indirectly controlled by an        expanded version 800 of the combined Unified Bandwidth Manager        and Communications Silo Environment entity 700 of FIG. 13 b.

FIG. 37 depicts an example where an exemplary node 103 within anexemplary mobile communications network 100 comprises a router 950linking network data flows inside the node (for example 901, 902, 911,912, 921, 922) with network data flows outside the node (for example113, 114, 115, 116). In the example of FIG. 37, some network data flows901, 911, 921 (denoted as solid lines) are under the (direct orindirect) bandwidth allocation control of the combined Unified BandwidthManager and Communications Silo Environment entity 800, while othernetwork data flows 902, 912, 922 (denoted as dashed lines) are not underthe (direct or indirect) bandwidth allocation control of the combinedUnified Bandwidth Manager and Communications Silo Environment entity800. Of the network data flows 901, 911, 921 under (direct or indirect)bandwidth allocation control by the combined Unified Bandwidth Managerand Communications Silo Environment entity 800, some 901 transactdirectly with the router as inherent, as option, as fall-back, etc. inthe a given first individual or first collection of network-basedcomputer and communications service(s), application(s), orcapability(ies). Other network data flows 911 under (direct or indirect)bandwidth allocation control by the combined Unified Bandwidth Managerand Communications Silo Environment entity 800 involve action of asession provided by a communications processing resource 910 before orafter the router 950 and have an associated corresponding network flow921 between the communications processing resource 910 and the router950. In some situations, implementations, or embodiments provided for bythe invention, the communications processing resource 910 additionallycan support network flows 912, 922 not under (direct or indirect)bandwidth allocation control by the combined Unified Bandwidth Managerand Communications Silo Environment entity 800. The communicationsprocessing resource 910 depicted in FIG. 37 can, for example, provideone or more of

-   -   a network firewall traversal session,    -   a signal transcoding session,    -   a media stream encryption session        among many other possibilities as suggested above.

For the example considered here, a bandwidth allocation for network flow901 does not require a session allocation of the communicationsprocessing resource 910, but a bandwidth allocation for network flow 911does require a session allocation of the communications processingresource 910 as well as a bandwidth allocation for the collateralnetwork flow 921. The communications processing resource 910 willprovide up to a maximum number of simultaneous sessions. In some cases,the maximum number of simultaneous sessions can be somewhat variable,driven by computational loading for example. More commonly, the maximumnumber of simultaneous sessions is a fixed value implemented in thesoftware of the communications processing resource 910. For example:

-   -   A transcoder server can only permit a maximum number of        simultaneous VoIP and/or Video transcoding sessions;    -   A network firewall can only permit a maximum number of        simultaneous VoIP and/or Video traversal sessions;    -   A media stream encryption server can only permit a maximum        number of simultaneous VoIP and/or Video encryption sessions.

Additionally, albeit for different reasons, implementations of aprotocol translating gateway can only permit a maximum number ofsessions even though such a gateway is not actively handling mediaflows.

Exemplary Unified Bandwidth Manager features and embodiments taught inpending U.S. patent application Ser. No. 12/572,226 provide for controlsystems and human operator modeling tools leveraging a multiserviceblocking model. Because of the typical statistics of sessions andproperties of the associated aggregated request traffic, the aggregatedservice requests advantageously closely conform to a Poisson arrivalprocess. Session statistics also typically lead to exponential holdingtimes, although this is not strictly required for the resultingstochastic dynamics to behave as a product-form network. The resultingdynamics have the both remarkable property that if system behavior canbe structured in such a fashion as to truncate the state-space, theremaining permitted states and state-transitions maintain their relativeprobability ratios and thus the resulting dynamics only requirescalculation of the normalization factor. This normalization factor iscalculated by summing all of the relative probabilities assuming anynormalization and finding the normalization factor (for examplereciprocal of the sum) that cause the sums of all probabilities to equala value of 1. This can advantageously exploited in the present inventionby structuring the allocations of sessions from communicationsprocessing resources (such as element 910 in FIG. 37) so as to impose atruncation on the product-form state space in such a way that theprobabilities for the permitted states and/or state-transitions can beexplicitly algebraically summed and used to solve for the factor neededto normalize the state and/or state-transition probabilities.

As a result, the system and method of the present invention allow forinclusion of associated communications processing resources along withbandwidth allocations. The system and method of the present inventionthus delivers a powerful enhancement to the exemplary Unified BandwidthManager features and embodiments taught in pending U.S. patentapplication Ser. No. 12/572,226.

Additionally, these powerful new features are added by simply “tappinginto” the control and modeling framework taught in pending U.S. patentapplication Ser. No. 12/572,226 with state-space modifications (forexample, addition of an additional vector space coordinate) and/ortruncations of the product-form state-space and/or state-transitions.FIG. 38 shows exemplary state-space modifications (which may or may notbe necessary, depending on the starting point) and/or truncations of theproduct-form state-space and/or state-transitions).

In this example, the given service, application, etc. (for example, aVoIP call, video call, etc.) is assumed to require an allocation of auniform-sized “quanta” of bandwidth. This quanta can, for example, befixed, represent an average, or be a function of an average togetherwith higher statistical moments of underlying packet traffic. Someinstances (for example VoIP call, video call) can require acommunications processing resource (such as element 910 in FIG. 37)session while others do not. For this particular example, one could pairthe session of communications processing resource session with theassociated bandwidth allocation. In some situations this can include anadded bandwidth element (for example, recognizing the extra bandwidthrequired by the pair of flows 911 and 921 as compared to the flow 901).FIG. 38 shows a case wherein the maximum number of bandwidth quanta islarger than the number of sessions made available by the communicationsprocessing resource. If further, for example, there is only onebandwidth quanta used in each session pairing, one could envision thefollowing example:

-   -   One bandwidth quanta used in each session pairing    -   Max of 10 pairings (horizontal state-space axis)    -   Max of 16 bandwidth quanta

The state-space truncation is then governed by the following:

-   -   If there are no requests for pairings, then all 16 bandwidth        quanta are available for non-pairing call allocations.    -   For each pairing allocated, there is one fewer bandwidth quanta        available for non-pairing call allocations.    -   If all ten pairings are allocated, no more pairings are possible        and only 6 bandwidth quanta are available for non-pairing call        allocations.

Thus the truncated state space has the shape depicted in FIG. 38.Variations of the assumptions result in associated variations, forexample the location of the extremal vertex, slope of the lines, etc.Similarly, for more complex arrangements, a higher-order vector space isused in the product-form state space, and the truncation boundary is aconvex hull.

In an embodiment, the invention provides for adaptations of protocolgateways and transcoders to support aspects of highly scalablemulti-service environments comprising video for mobile devices. In anembodiment, the invention provides for adaptations of video multipointbridges to support aspects of highly scalable multi-service environmentscomprising video for mobile devices. In an embodiment, the inventionprovides for adaptations of real-time data collaboration to supportaspects of highly scalable multi-service environment for mobile devices.In an embodiment, the invention provides for adaptations of real-timedata collaboration multipoint bridges to support aspects of highlyscalable multi-service environments comprising video for mobile devices.

8. Adapting Thin-Client AV Methods and Systems to Mobile Networks

In an embodiment, the invention provides for adaptations of thin-clientAV methods and systems, such as taught in pending U.S. patentapplication Ser. Nos. 12/828,249 and Ser. No. 12/828,253, to supportaspects of highly scalable multi-service environments comprising videofor mobile devices. Attention is again directed to FIG. 6 which depictsadaptations and combinations of multiservice bandwidth managementtechnology, AN gateway technologies, and thin-client A/V technologies tocreate multiservice mobile networks and devices supporting 2-way video.Although many aspects of the aforementioned thin-client technology canbe applied to mobile communications, a first aspect of particularinterest is multi-component partitioning capabilities. A second aspectof particular interest is auto-dividing capabilities.

CLOSING

The terms “certain embodiments”, “an embodiment”, “embodiment”,“embodiments”, “the embodiment”, “the embodiments”, “one or moreembodiments”, “some embodiments”, and “one embodiment” mean one or more(but not all) embodiments unless expressly specified otherwise. Theterms “including”, “comprising”, “having” and variations thereof mean“including but not limited to”, unless expressly specified otherwise.The enumerated listing of items does not imply that any or all of theitems are mutually exclusive, unless expressly specified otherwise. Theterms “a”, “an” and “the” mean “one or more”, unless expressly specifiedotherwise.

While the invention has been described in detail with reference todisclosed embodiments, various modifications within the scope of theinvention will be apparent to those of ordinary skill in thistechnological field. It is to be appreciated that features describedwith respect to one embodiment typically can be applied to otherembodiments without departing from the spirit or scope of the invention.It is to be appreciated that features described with respect to oneembodiment typically may be applied to other embodiments. It is intendedthat the specification and examples be considered as exemplary only,with the true scope and spirit of the invention being indicated by thefollowing claims.

The invention can be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. The presentembodiments are therefore to be considered in all respects asillustrative and not restrictive, the scope of the invention beingindicated by the appended claims rather than by the foregoingdescription, and all changes which come within the meaning and range ofequivalency of the claims are therefore intended to be embraced therein.

Although exemplary embodiments have been provided in detail, variouschanges, substitutions and alternations could be made thereto withoutdeparting from spirit and scope of the disclosed subject matter asdefined by the appended claims. Variations described for the embodimentsmay be realized singly or in any combination desirable for eachparticular application. Thus particular limitations and embodimentenhancements described herein, which may have particular advantages to aparticular application, need not be used for all applications. Also, notall limitations need be implemented in methods, systems, and apparatusesincluding one or more concepts described with relation to the providedembodiments. Therefore, the invention properly is to be construed withreference to the claims.

REFERENCES

-   [X1] L. Ludwig, “Adaptive Links—A Methodology for Dynamic Bandwidth    Allocation,” Proc. 6th International Conference on Computer    Communications, London, September 1982.-   [X2] J. S. Kaufman, “Blocking in a Shared Resource Environment,”    IEEE Transactions on Communications, vol. COM-29, No. 10, October    1981 pp. 1474-1481.-   [X3] K. W. Ross, Multiservice Loss Models for Broadband    Telecommunication Networks, Springer, 1995, ISBN 3-540-19918-7.-   [X4] Miguel Barreiros and Peter Lundqvist, QOS-Enabled Networks:    Tools and Foundations, John Wiley & Sons, Ltd, 2010 (ISBN-10    0470686979; ISBN-13 978-0-470-68697-3).-   [X5] Cisco Systems, “Cisco Catalyst 2950 Series Switches with    Enhanced Image SW”    http://www.cisco.com/en/US/prod/collateral/switches/ps5718/ps628/product_data_sheet09186a00801cfb64_ps6558_Products_Data_Sheet.html    (visited Jun. 29, 2011).-   [X6] Juniper Networks, “EX Server Ethernet Switches: QoS Enabling    the Enterprise,”    http://www.juniper.net/us/en/local/pdf/whitepapers/2000255-en.pdf    (visited Jun. 29, 2011).-   [X7] Juniper Networks, “JUNOSe Policy and QoS Configuration    Guide—Configuring Quality of Service,”    http://www.juniper.net/techpubs/software/erx/junose61/swconfig-policy-qos/frameset.htm    (visited Jun. 29, 2011).-   [Z1] Zhang, Wu, Lui, “Stability and sensitivity for congestion    control in wireless mesh networks with time varying link    capacities,” Ad Hoc Networks, Volume 5, Issue 6 (August 2007) Pages:    769-785.-   [Z2] Sins, Triantafyllidou, “Seamless Congestion Control over Wired    and Wireless IEEE 802.11 Networks,” Wireless IEEE 802.11 Networks.    Proc. of Networking, 2004.-   [Z3] Acharya, et al., “Congestion-Aware Rate Adaptation in Wireless    Networks: A Measurement-Driven Approach,” 2007.-   [Z4] Zhu, Han, Girod, “Congestion-Aware Rate Allocation For    Multipath Video Streaming . . . ,” IEEE International Conference on    Image Processing, 2004.

What is claimed is:
 1. A bandwidth management system formultiple-service mobile networks for use with a plurality of instancesof mobile communications devices, the bandwidth management systemcomprising: at least one first interface, the at least one firstinterface for receiving call/session state information from a pluralityof communications silos using a mobile network, each communications siloproviding at least one communications service; at least one secondinterface, the at least one second interface for transmitting controlmessages to the plurality of communications silos, the control messagescomprising call/session admission control settings and application QoSparameter settings; at least one network monitor for measuringpacket-level network transport and producing packet-level networktransport measurement information responsive to packet-level networktransport processes in the mobile network; and at least one controlsystem in communications with the at least first and second interfaces,the control system for performing computations responsive to thereceived call/session state information and packet-level networktransport measurement information, the control system producing thecontrol messages to be transmitted to the plurality of communicationssilos, wherein the control system controls both call/session admissioncontrol settings and application QoS parameter settings responsive tocall/session state information and packet-level network transportmeasurement information; and wherein at least one communications servicefrom at least one communications silo involving the transport ofreal-time two-way video.